{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/cabinas_jop_log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}19 Sep 2023, 12:34:42
{txt}
{com}. 
{txt}end of do-file

{com}. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"
{txt}
{com}. cd "~/Dropbox/JOP third submission/JOP replication/"
{res}/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication
{txt}
{com}. 
{txt}end of do-file

{com}. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. 
. * Open dataset
. use 01_data/cses2_3.dta, clear
{txt}( )

{com}. 
. * Run analyses
. regr like_party pp_dummy, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   755,529
                                                {txt}F(1, 132944)      =  {res}    85.78
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0001
                                                {txt}Root MSE          =    {res} 2.9582

{txt}{ralign 78:(Std. err. adjusted for {res:132,945} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  like_party{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}-.6012691{col 26}{space 2} .0649205{col 37}{space 1}   -9.26{col 46}{space 3}0.000{col 54}{space 4}-.7285121{col 67}{space 3}-.4740262
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.294574{col 26}{space 2}  .004367{col 37}{space 1}  983.41{col 46}{space 3}0.000{col 54}{space 4} 4.286014{col 67}{space 3} 4.303133
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store like_party_1
{txt}
{com}. estadd local  Sample "All parties"

{txt}added macro:
             e(Sample) : "{res:All parties}"

{com}. 
. regr like_party pp_dummy if cses_wave == 2, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   300,485
                                                {txt}F(1, 59652)       =  {res}    56.48
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0002
                                                {txt}Root MSE          =    {res} 2.9906

{txt}{ralign 78:(Std. err. adjusted for {res:59,653} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  like_party{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}-.6956235{col 26}{space 2} .0925582{col 37}{space 1}   -7.52{col 46}{space 3}0.000{col 54}{space 4}-.8770379{col 67}{space 3} -.514209
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.386659{col 26}{space 2} .0063693{col 37}{space 1}  688.72{col 46}{space 3}0.000{col 54}{space 4} 4.374175{col 67}{space 3} 4.399143
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store like_party_2
{txt}
{com}. estadd local  Sample "All parties"

{txt}added macro:
             e(Sample) : "{res:All parties}"

{com}. 
. regr like_party pp_dummy if cses_wave == 3, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   455,044
                                                {txt}F(1, 73291)       =  {res}    34.92
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0001
                                                {txt}Root MSE          =    {res}  2.935

{txt}{ralign 78:(Std. err. adjusted for {res:73,292} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  like_party{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}-.5383023{col 26}{space 2} .0910883{col 37}{space 1}   -5.91{col 46}{space 3}0.000{col 54}{space 4}-.7168351{col 67}{space 3}-.3597695
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.233843{col 26}{space 2} .0058963{col 37}{space 1}  718.05{col 46}{space 3}0.000{col 54}{space 4} 4.222286{col 67}{space 3} 4.245399
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store like_party_3
{txt}
{com}. estadd local  Sample "All parties"

{txt}added macro:
             e(Sample) : "{res:All parties}"

{com}. 
. regr like_party pp_dummy if center_right == 1, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   278,116
                                                {txt}F(1, 122079)      =  {res}   128.09
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0005
                                                {txt}Root MSE          =    {res} 2.9712

{txt}{ralign 78:(Std. err. adjusted for {res:122,080} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  like_party{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}-.7358745{col 26}{space 2} .0650194{col 37}{space 1}  -11.32{col 46}{space 3}0.000{col 54}{space 4}-.8633114{col 67}{space 3}-.6084375
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.429179{col 26}{space 2} .0069954{col 37}{space 1}  633.15{col 46}{space 3}0.000{col 54}{space 4} 4.415468{col 67}{space 3}  4.44289
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store like_party_4
{txt}
{com}. estadd local  Sample "Center-right parties"

{txt}added macro:
             e(Sample) : "{res:Center-right parties}"

{com}. 
. regr like_party pp_dummy if center_right == 1 &  cses_wave == 2, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   116,993
                                                {txt}F(1, 56199)       =  {res}    85.43
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0008
                                                {txt}Root MSE          =    {res} 2.9843

{txt}{ralign 78:(Std. err. adjusted for {res:56,200} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  like_party{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} -.857029{col 26}{space 2} .0927229{col 37}{space 1}   -9.24{col 46}{space 3}0.000{col 54}{space 4}-1.038766{col 67}{space 3}-.6752914
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 4.548065{col 26}{space 2} .0107512{col 37}{space 1}  423.03{col 46}{space 3}0.000{col 54}{space 4} 4.526992{col 67}{space 3} 4.569137
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store like_party_5
{txt}
{com}. estadd local  Sample "Center-right parties"

{txt}added macro:
             e(Sample) : "{res:Center-right parties}"

{com}. 
. regr like_party pp_dummy if center_right == 1 &  cses_wave == 3, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   161,123
                                                {txt}F(1, 65879)       =  {res}    50.40
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0003
                                                {txt}Root MSE          =    {res} 2.9587

{txt}{ralign 78:(Std. err. adjusted for {res:65,880} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  like_party{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}-.6475394{col 26}{space 2} .0912121{col 37}{space 1}   -7.10{col 46}{space 3}0.000{col 54}{space 4}-.8263152{col 67}{space 3}-.4687636
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  4.34308{col 26}{space 2} .0091995{col 37}{space 1}  472.10{col 46}{space 3}0.000{col 54}{space 4} 4.325049{col 67}{space 3} 4.361111
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store like_party_6
{txt}
{com}. estadd local  Sample "Center-right parties"

{txt}added macro:
             e(Sample) : "{res:Center-right parties}"

{com}. 
. * Make table
. esttab like_party_1 like_party_2 like_party_3 like_party_4 like_party_5 like_party_6 using 03_tables/table1.tex, tex se replace mtitles ("CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3") keep(pp_dummy _cons) coeflabels (pp_dummy "PP (dummy)" _cons "Constant") s(Sample, label("Sample")) star(* 0.10 ** 0.05 *** 0.01) addnotes("Standard errors are clustered by respondent") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/table1.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/table2.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. 
. * Open dataset
. use 01_data/cses2_3.dta, clear
{txt}( )

{com}. 
. * Run analyses
. regr difference_voter_expert pp_dummy

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}   628,003
{txt}{hline 13}{c +}{hline 34}   F(1, 628001)    = {res}   201.34
{txt}       Model {c |} {res} 1314.37877         1  1314.37877   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 4099714.99   628,001  6.52819819   {txt}R-squared       ={res}    0.0003
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0003
{txt}       Total {c |} {res} 4101029.37   628,002  6.53028075   {txt}Root MSE        =   {res}  2.555

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}difference~t{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .7711658{col 26}{space 2} .0543481{col 37}{space 1}   14.19{col 46}{space 3}0.000{col 54}{space 4} .6646454{col 67}{space 3} .8776863
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0088161{col 26}{space 2} .0032299{col 37}{space 1}    2.73{col 46}{space 3}0.006{col 54}{space 4} .0024857{col 67}{space 3} .0151466
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store lr_party_1
{txt}
{com}. estadd local  Sample "All parties"

{txt}added macro:
             e(Sample) : "{res:All parties}"

{com}. 
. regr difference_voter_expert pp_dummy if cses_wave == 2, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   235,726
                                                {txt}F(1, 46951)       =  {res}   209.22
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0005
                                                {txt}Root MSE          =    {res} 2.5489

{txt}{ralign 78:(Std. err. adjusted for {res:46,952} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}difference~t{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .8237755{col 26}{space 2} .0569516{col 37}{space 1}   14.46{col 46}{space 3}0.000{col 54}{space 4} .7121495{col 67}{space 3} .9354015
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.0035806{col 26}{space 2} .0060168{col 37}{space 1}   -0.60{col 46}{space 3}0.552{col 54}{space 4}-.0153737{col 67}{space 3} .0082125
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store lr_party_2
{txt}
{com}. estadd local  Sample "All parties"

{txt}added macro:
             e(Sample) : "{res:All parties}"

{com}. 
. regr difference_voter_expert pp_dummy if cses_wave == 3, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   392,277
                                                {txt}F(1, 65187)       =  {res}   203.77
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0002
                                                {txt}Root MSE          =    {res} 2.5587

{txt}{ralign 78:(Std. err. adjusted for {res:65,188} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}difference~t{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .7220415{col 26}{space 2} .0505811{col 37}{space 1}   14.27{col 46}{space 3}0.000{col 54}{space 4} .6229024{col 67}{space 3} .8211806
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0162505{col 26}{space 2} .0051645{col 37}{space 1}    3.15{col 46}{space 3}0.002{col 54}{space 4}  .006128{col 67}{space 3}  .026373
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store lr_party_3
{txt}
{com}. estadd local  Sample "All parties"

{txt}added macro:
             e(Sample) : "{res:All parties}"

{com}. 
. regr difference_voter_expert pp_dummy if center_right == 1, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   238,027
                                                {txt}F(1, 104322)      =  {res}   904.48
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0018
                                                {txt}Root MSE          =    {res} 2.5867

{txt}{ralign 78:(Std. err. adjusted for {res:104,323} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}difference~t{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} 1.157762{col 26}{space 2} .0384964{col 37}{space 1}   30.07{col 46}{space 3}0.000{col 54}{space 4}  1.08231{col 67}{space 3} 1.233215
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.3777803{col 26}{space 2} .0068607{col 37}{space 1}  -55.06{col 46}{space 3}0.000{col 54}{space 4}-.3912271{col 67}{space 3}-.3643335
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store lr_party_4
{txt}
{com}. estadd local  Sample "Center-right parties"

{txt}added macro:
             e(Sample) : "{res:Center-right parties}"

{com}. 
. regr difference_voter_expert pp_dummy if center_right == 1 &  cses_wave == 2, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}    95,664
                                                {txt}F(1, 45698)       =  {res}   357.63
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0022
                                                {txt}Root MSE          =    {res} 2.5207

{txt}{ralign 78:(Std. err. adjusted for {res:45,699} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}difference~t{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} 1.085768{col 26}{space 2} .0574145{col 37}{space 1}   18.91{col 46}{space 3}0.000{col 54}{space 4} .9732352{col 67}{space 3} 1.198302
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.2655736{col 26}{space 2} .0103747{col 37}{space 1}  -25.60{col 46}{space 3}0.000{col 54}{space 4}-.2859081{col 67}{space 3}-.2452391
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store lr_party_5
{txt}
{com}. estadd local  Sample "Center-right parties"

{txt}added macro:
             e(Sample) : "{res:Center-right parties}"

{com}. 
. regr difference_voter_expert pp_dummy if center_right == 1 &  cses_wave == 3, cluster(respondent_code)

{txt}Linear regression                               Number of obs     = {res}   142,363
                                                {txt}F(1, 58623)       =  {res}   544.22
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0016
                                                {txt}Root MSE          =    {res} 2.6275

{txt}{ralign 78:(Std. err. adjusted for {res:58,624} clusters in {res:respondent_code})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}difference~t{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} 1.191157{col 26}{space 2} .0510599{col 37}{space 1}   23.33{col 46}{space 3}0.000{col 54}{space 4} 1.091079{col 67}{space 3} 1.291234
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-.4528646{col 26}{space 2} .0091018{col 37}{space 1}  -49.76{col 46}{space 3}0.000{col 54}{space 4}-.4707041{col 67}{space 3}-.4350251
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store lr_party_6
{txt}
{com}. estadd local  Sample "Center-right parties"

{txt}added macro:
             e(Sample) : "{res:Center-right parties}"

{com}. 
. * Make table
. esttab lr_party_1 lr_party_2 lr_party_3 lr_party_4 lr_party_5 lr_party_6 using 03_tables/table2.tex, tex se replace mtitles ("CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3") keep(pp_dummy _cons) coeflabels (pp_dummy "PP (dummy)" _cons "Constant") s(Sample, label("Sample")) star(* 0.10 ** 0.05 *** 0.01) addnotes("Standard errors are clustered by respondent") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/table2.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/table4.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. * Run analyses
. 
. * Model 1
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32160 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,474
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59236{txt}){col 67}= {res}  10596.64
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4046
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,237{txt}{col 51}Root MSE{col 67}= {res}    5.2282

{txt}{ralign 84:(Std. err. adjusted for {res:59,237} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.121899{col 32}{space 2}  .062844{col 43}{space 1}  -97.41{col 52}{space 3}0.000{col 60}{space 4}-6.245074{col 73}{space 3}-5.998725
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0404565{col 32}{space 2} .0712617{col 43}{space 1}    0.57{col 52}{space 3}0.570{col 60}{space 4}-.0992168{col 73}{space 3} .1801298
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.167986{col 32}{space 2} .6933568{col 43}{space 1}    1.68{col 52}{space 3}0.092{col 60}{space 4}-.1909961{col 73}{space 3} 2.526968
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.145957{col 32}{space 2} 1.121938{col 43}{space 1}   -2.80{col 52}{space 3}0.005{col 60}{space 4}-5.344961{col 73}{space 3} -.946953
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.43706{col 32}{space 2} .0151892{col 43}{space 1} 1806.35{col 52}{space 3}0.000{col 60}{space 4} 27.40729{col 73}{space 3} 27.46683
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59237{col 38}{space 1}    59237{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_pp_ddd
{txt}
{com}. 
. * Model 2
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,986
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  76157{txt}){col 67}= {res}  45033.49
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8200
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7136
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4234
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,158{txt}{col 51}Root MSE{col 67}= {res}    9.4294

{txt}{ralign 84:(Std. err. adjusted for {res:76,158} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.92846{col 32}{space 2} .0686972{col 43}{space 1} -188.19{col 52}{space 3}0.000{col 60}{space 4} -13.0631{col 73}{space 3}-12.79381
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.027174{col 32}{space 2} .0779292{col 43}{space 1}  -13.18{col 52}{space 3}0.000{col 60}{space 4}-1.179914{col 73}{space 3}-.8744326
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4127518{col 32}{space 2} .5894408{col 43}{space 1}    0.70{col 52}{space 3}0.484{col 60}{space 4}-.7425492{col 73}{space 3} 1.568053
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.454152{col 32}{space 2} 1.008371{col 43}{space 1}   -2.43{col 52}{space 3}0.015{col 60}{space 4}-4.430553{col 73}{space 3}-.4777504
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.61937{col 32}{space 2} .0115142{col 43}{space 1} 3006.67{col 52}{space 3}0.000{col 60}{space 4}  34.5968{col 73}{space 3} 34.64194
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76158{col 38}{space 1}    76158{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_pp_ddd
{txt}
{com}. 
. * Model 3
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,986
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  76157{txt}){col 67}= {res}  52208.63
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9147
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8643
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7267
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,158{txt}{col 51}Root MSE{col 67}= {res}    6.4917

{txt}{ralign 84:(Std. err. adjusted for {res:76,158} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.32835{col 32}{space 2} .0738505{col 43}{space 1} -275.26{col 52}{space 3}0.000{col 60}{space 4} -20.4731{col 73}{space 3}-20.18361
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2106771{col 32}{space 2} .0751797{col 43}{space 1}    2.80{col 52}{space 3}0.005{col 60}{space 4} .0633253{col 73}{space 3} .3580289
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7924392{col 32}{space 2} .5892418{col 43}{space 1}    1.34{col 52}{space 3}0.179{col 60}{space 4} -.362472{col 73}{space 3}  1.94735
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.692002{col 32}{space 2} 1.008169{col 43}{space 1}   -3.66{col 52}{space 3}0.000{col 60}{space 4}-5.668008{col 73}{space 3}-1.715997
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.04042{col 32}{space 2} .0365116{col 43}{space 1} -384.55{col 52}{space 3}0.000{col 60}{space 4}-14.11198{col 73}{space 3}-13.96885
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.23033{col 32}{space 2} .0235892{col 43}{space 1} 1747.85{col 52}{space 3}0.000{col 60}{space 4}  41.1841{col 73}{space 3} 41.27657
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76158{col 38}{space 1}    76158{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_pp_ddd
{txt}
{com}. 
. * Placebo
. reghdfe pp_voteshare_lag post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 23221 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   105,890
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  52944{txt}){col 67}= {res}  32096.26
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9349
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8698
{txt}{col 51}Within R-sq.{col 67}= {res}    0.6984
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    52,945{txt}{col 51}Root MSE{col 67}= {res}    6.4978

{txt}{ralign 84:(Std. err. adjusted for {res:52,945} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}  pp_voteshare_lag{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-14.09829{col 32}{space 2} .0809325{col 43}{space 1} -174.20{col 52}{space 3}0.000{col 60}{space 4}-14.25692{col 73}{space 3}-13.93966
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1718456{col 32}{space 2} .0924712{col 43}{space 1}    1.86{col 52}{space 3}0.063{col 60}{space 4}-.0093989{col 73}{space 3}   .35309
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.025296{col 32}{space 2} .5664412{col 43}{space 1}   -1.81{col 52}{space 3}0.070{col 60}{space 4}-2.135526{col 73}{space 3} .0849338
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-.9234955{col 32}{space 2} .9922132{col 43}{space 1}   -0.93{col 52}{space 3}0.352{col 60}{space 4}-2.868242{col 73}{space 3} 1.021251
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.33486{col 32}{space 2} .0199681{col 43}{space 1} 2070.04{col 52}{space 3}0.000{col 60}{space 4} 41.29572{col 73}{space 3} 41.37399
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    52945{col 38}{space 1}    52945{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store placebo_pp_ddd
{txt}
{com}. 
. * Make table
. esttab twoperiods_pp_ddd prepost_pp_ddd threeperiods_pp_ddd placebo_pp_ddd using 03_tables/table4.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019" "Placebo lagged outcome")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/table4.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/table5.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Run analyses
. 
. regr cabine_use pp_dummy, r

{txt}Linear regression                               Number of obs     = {res}     1,847
                                                {txt}F(1, 1845)        =  {res}    11.55
                                                {txt}Prob > F          = {res}    0.0007
                                                {txt}R-squared         = {res}    0.0063
                                                {txt}Root MSE          =    {res} .49543

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}  .113812{col 26}{space 2} .0334868{col 37}{space 1}    3.40{col 46}{space 3}0.001{col 54}{space 4}  .048136{col 67}{space 3} .1794881
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .427044{col 26}{space 2} .0124118{col 37}{space 1}   34.41{col 46}{space 3}0.000{col 54}{space 4} .4027014{col 67}{space 3} .4513866
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_nocontrols
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. estadd local FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. regr cabine_use pp_dummy i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,847
                                                {txt}F(19, 1827)       =  {res}    45.56
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2140
                                                {txt}Root MSE          =    {res} .44278

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                   cabine_use{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}pp_dummy {c |}{col 31}{res}{space 2} .0620417{col 43}{space 2} .0301818{col 54}{space 1}    2.06{col 63}{space 3}0.040{col 71}{space 4} .0028473{col 84}{space 3} .1212361
{txt}{space 29} {c |}
{space 25}CCAA {c |}
{space 22}Aragón  {c |}{col 31}{res}{space 2}-.0897035{col 43}{space 2} .0645425{col 54}{space 1}   -1.39{col 63}{space 3}0.165{col 71}{space 4}-.2162884{col 84}{space 3} .0368813
{txt}{space 4}Asturias (Principado de)  {c |}{col 31}{res}{space 2}-.2223241{col 43}{space 2} .0662738{col 54}{space 1}   -3.35{col 63}{space 3}0.001{col 71}{space 4}-.3523045{col 84}{space 3}-.0923437
{txt}{space 13}Balears (Illes)  {c |}{col 31}{res}{space 2}-.1321739{col 43}{space 2} .0631238{col 54}{space 1}   -2.09{col 63}{space 3}0.036{col 71}{space 4}-.2559764{col 84}{space 3}-.0083715
{txt}{space 20}Canarias  {c |}{col 31}{res}{space 2} .3790184{col 43}{space 2} .0477885{col 54}{space 1}    7.93{col 63}{space 3}0.000{col 71}{space 4} .2852926{col 84}{space 3} .4727441
{txt}{space 19}Cantabria  {c |}{col 31}{res}{space 2} .0189394{col 43}{space 2} .0632698{col 54}{space 1}    0.30{col 63}{space 3}0.765{col 71}{space 4}-.1051493{col 84}{space 3} .1430282
{txt}{space 10}Castilla-La Mancha  {c |}{col 31}{res}{space 2} .0812481{col 43}{space 2} .0671631{col 54}{space 1}    1.21{col 63}{space 3}0.227{col 71}{space 4}-.0504765{col 84}{space 3} .2129726
{txt}{space 13}Castilla y León  {c |}{col 31}{res}{space 2} .0503454{col 43}{space 2}  .063747{col 54}{space 1}    0.79{col 63}{space 3}0.430{col 71}{space 4}-.0746792{col 84}{space 3}   .17537
{txt}{space 20}Cataluña  {c |}{col 31}{res}{space 2}-.4494289{col 43}{space 2} .0345086{col 54}{space 1}  -13.02{col 63}{space 3}0.000{col 71}{space 4}-.5171093{col 84}{space 3}-.3817484
{txt}{space 8}Comunitat Valenciana  {c |}{col 31}{res}{space 2}-.0716436{col 43}{space 2} .0512482{col 54}{space 1}   -1.40{col 63}{space 3}0.162{col 71}{space 4}-.1721548{col 84}{space 3} .0288675
{txt}{space 17}Extremadura  {c |}{col 31}{res}{space 2} .2120628{col 43}{space 2}  .057937{col 54}{space 1}    3.66{col 63}{space 3}0.000{col 71}{space 4} .0984332{col 84}{space 3} .3256924
{txt}{space 21}Galicia  {c |}{col 31}{res}{space 2}-.0268084{col 43}{space 2} .0629393{col 54}{space 1}   -0.43{col 63}{space 3}0.670{col 71}{space 4} -.150249{col 84}{space 3} .0966322
{txt}{space 7}Madrid (Comunidad de)  {c |}{col 31}{res}{space 2}-.4184945{col 43}{space 2} .0369599{col 54}{space 1}  -11.32{col 63}{space 3}0.000{col 71}{space 4}-.4909827{col 84}{space 3}-.3460064
{txt}{space 10}Murcia (Región de)  {c |}{col 31}{res}{space 2} .1267141{col 43}{space 2} .0616841{col 54}{space 1}    2.05{col 63}{space 3}0.040{col 71}{space 4} .0057354{col 84}{space 3} .2476929
{txt}Navarra (Comunidad Foral de)  {c |}{col 31}{res}{space 2}-.0769993{col 43}{space 2} .0839086{col 54}{space 1}   -0.92{col 63}{space 3}0.359{col 71}{space 4}-.2415662{col 84}{space 3} .0875676
{txt}{space 18}País Vasco  {c |}{col 31}{res}{space 2}-.0916946{col 43}{space 2} .0718691{col 54}{space 1}   -1.28{col 63}{space 3}0.202{col 71}{space 4}-.2326487{col 84}{space 3} .0492596
{txt}{space 18}Rioja (La)  {c |}{col 31}{res}{space 2} .0601875{col 43}{space 2} .0697591{col 54}{space 1}    0.86{col 63}{space 3}0.388{col 71}{space 4}-.0766285{col 84}{space 3} .1970034
{txt}{space 2}Ceuta (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .3058338{col 43}{space 2} .0656224{col 54}{space 1}    4.66{col 63}{space 3}0.000{col 71}{space 4} .1771309{col 84}{space 3} .4345367
{txt}Melilla (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .1487341{col 43}{space 2} .1142908{col 54}{space 1}    1.30{col 63}{space 3}0.193{col 71}{space 4}-.0754203{col 84}{space 3} .3728884
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .5389007{col 43}{space 2} .0296552{col 54}{space 1}   18.17{col 63}{space 3}0.000{col 71}{space 4} .4807391{col 84}{space 3} .5970624
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. estadd local  FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. regr cabine_use pp_dummy female i.income age age_sq i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(25, 1330)       =  {res}    16.73
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1167
                                                {txt}Root MSE          =    {res} .47399

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1314563{col 45}{space 2}   .03732{col 56}{space 1}    3.52{col 65}{space 3}0.000{col 73}{space 4} .0582438{col 86}{space 3} .2046687
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0158409{col 45}{space 2} .0277424{col 56}{space 1}   -0.57{col 65}{space 3}0.568{col 73}{space 4}-.0702646{col 86}{space 3} .0385828
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0380048{col 45}{space 2}  .091719{col 56}{space 1}    0.41{col 65}{space 3}0.679{col 73}{space 4}-.1419248{col 86}{space 3} .2179343
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0014734{col 45}{space 2} .0589043{col 56}{space 1}    0.03{col 65}{space 3}0.980{col 73}{space 4}-.1140822{col 86}{space 3} .1170289
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0255149{col 45}{space 2} .0484068{col 56}{space 1}   -0.53{col 65}{space 3}0.598{col 73}{space 4} -.120477{col 86}{space 3} .0694471
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0573133{col 45}{space 2} .0460066{col 56}{space 1}   -1.25{col 65}{space 3}0.213{col 73}{space 4}-.1475668{col 86}{space 3} .0329402
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0589429{col 45}{space 2} .0480938{col 56}{space 1}   -1.23{col 65}{space 3}0.221{col 73}{space 4}-.1532908{col 86}{space 3} .0354051
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0387394{col 45}{space 2} .0584283{col 56}{space 1}   -0.66{col 65}{space 3}0.507{col 73}{space 4}-.1533611{col 86}{space 3} .0758823
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.1229924{col 45}{space 2} .0799346{col 56}{space 1}   -1.54{col 65}{space 3}0.124{col 73}{space 4}-.2798039{col 86}{space 3} .0338192
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0919186{col 45}{space 2} .1104933{col 56}{space 1}    0.83{col 65}{space 3}0.406{col 73}{space 4}-.1248416{col 86}{space 3} .3086788
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4973995{col 45}{space 2} .0736127{col 56}{space 1}   -6.76{col 65}{space 3}0.000{col 73}{space 4}-.6418091{col 86}{space 3}-.3529898
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0920014{col 45}{space 2} .2522237{col 56}{space 1}   -0.36{col 65}{space 3}0.715{col 73}{space 4}-.5868011{col 86}{space 3} .4027984
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0026836{col 45}{space 2} .0047772{col 56}{space 1}    0.56{col 65}{space 3}0.574{col 73}{space 4} -.006688{col 86}{space 3} .0120553
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000539{col 45}{space 2} .0000491{col 56}{space 1}   -1.10{col 65}{space 3}0.273{col 73}{space 4}-.0001502{col 86}{space 3} .0000425
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0652387{col 45}{space 2} .1148669{col 56}{space 1}   -0.57{col 65}{space 3}0.570{col 73}{space 4}-.2905788{col 86}{space 3} .1601014
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1616461{col 45}{space 2} .1148042{col 56}{space 1}   -1.41{col 65}{space 3}0.159{col 73}{space 4}-.3868633{col 86}{space 3}  .063571
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2292419{col 45}{space 2}  .116196{col 56}{space 1}   -1.97{col 65}{space 3}0.049{col 73}{space 4}-.4571894{col 86}{space 3}-.0012945
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1206527{col 45}{space 2} .1155289{col 56}{space 1}   -1.04{col 65}{space 3}0.297{col 73}{space 4}-.3472915{col 86}{space 3}  .105986
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1323317{col 45}{space 2} .1169844{col 56}{space 1}   -1.13{col 65}{space 3}0.258{col 73}{space 4}-.3618258{col 86}{space 3} .0971625
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .010783{col 45}{space 2} .0626476{col 56}{space 1}    0.17{col 65}{space 3}0.863{col 73}{space 4}-.1121159{col 86}{space 3} .1336818
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1260727{col 45}{space 2} .0601022{col 56}{space 1}   -2.10{col 65}{space 3}0.036{col 73}{space 4}-.2439782{col 86}{space 3}-.0081672
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1207442{col 45}{space 2} .0638278{col 56}{space 1}   -1.89{col 65}{space 3}0.059{col 73}{space 4}-.2459584{col 86}{space 3}   .00447
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2403321{col 45}{space 2} .0610222{col 56}{space 1}   -3.94{col 65}{space 3}0.000{col 73}{space 4}-.3600423{col 86}{space 3}-.1206219
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3231655{col 45}{space 2}  .066451{col 56}{space 1}   -4.86{col 65}{space 3}0.000{col 73}{space 4}-.4535258{col 86}{space 3}-.1928053
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.5614998{col 45}{space 2} .0605895{col 56}{space 1}   -9.27{col 65}{space 3}0.000{col 73}{space 4}-.6803613{col 86}{space 3}-.4426384
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .8184492{col 45}{space 2} .1545058{col 56}{space 1}    5.30{col 65}{space 3}0.000{col 73}{space 4} .5153476{col 86}{space 3} 1.121551
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. estadd local  FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. regr cabine_use pp_dummy female i.income age age_sq i.education i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(43, 1312)       =  {res}    19.88
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2489
                                                {txt}Root MSE          =    {res} .44009

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0964548{col 45}{space 2}  .034805{col 56}{space 1}    2.77{col 65}{space 3}0.006{col 73}{space 4} .0281752{col 86}{space 3} .1647344
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0158589{col 45}{space 2} .0259646{col 56}{space 1}   -0.61{col 65}{space 3}0.541{col 73}{space 4}-.0667955{col 86}{space 3} .0350777
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0016742{col 45}{space 2} .0902907{col 56}{space 1}   -0.02{col 65}{space 3}0.985{col 73}{space 4}-.1788041{col 86}{space 3} .1754556
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0003704{col 45}{space 2} .0564329{col 56}{space 1}   -0.01{col 65}{space 3}0.995{col 73}{space 4} -.111079{col 86}{space 3} .1103383
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0328661{col 45}{space 2} .0446197{col 56}{space 1}   -0.74{col 65}{space 3}0.462{col 73}{space 4}-.1203999{col 86}{space 3} .0546678
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0447737{col 45}{space 2} .0423701{col 56}{space 1}   -1.06{col 65}{space 3}0.291{col 73}{space 4}-.1278942{col 86}{space 3} .0383468
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0222695{col 45}{space 2} .0447873{col 56}{space 1}   -0.50{col 65}{space 3}0.619{col 73}{space 4}-.1101321{col 86}{space 3} .0655931
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0051982{col 45}{space 2} .0532411{col 56}{space 1}    0.10{col 65}{space 3}0.922{col 73}{space 4}-.0992488{col 86}{space 3} .1096452
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} -.031228{col 45}{space 2} .0729213{col 56}{space 1}   -0.43{col 65}{space 3}0.669{col 73}{space 4}-.1742832{col 86}{space 3} .1118271
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1507493{col 45}{space 2} .1097734{col 56}{space 1}    1.37{col 65}{space 3}0.170{col 73}{space 4}-.0646013{col 86}{space 3} .3660999
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4246083{col 45}{space 2} .1784413{col 56}{space 1}   -2.38{col 65}{space 3}0.017{col 73}{space 4}-.7746697{col 86}{space 3}-.0745469
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0249654{col 45}{space 2} .2107723{col 56}{space 1}    0.12{col 65}{space 3}0.906{col 73}{space 4}-.3885222{col 86}{space 3}  .438453
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0005947{col 45}{space 2} .0045271{col 56}{space 1}   -0.13{col 65}{space 3}0.896{col 73}{space 4}-.0094758{col 86}{space 3} .0082863
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000169{col 45}{space 2} .0000471{col 56}{space 1}   -0.36{col 65}{space 3}0.721{col 73}{space 4}-.0001093{col 86}{space 3} .0000756
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} -.059104{col 45}{space 2} .1052495{col 56}{space 1}   -0.56{col 65}{space 3}0.575{col 73}{space 4}-.2655796{col 86}{space 3} .1473716
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1375116{col 45}{space 2} .1062387{col 56}{space 1}   -1.29{col 65}{space 3}0.196{col 73}{space 4} -.345928{col 86}{space 3} .0709047
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1661299{col 45}{space 2} .1078428{col 56}{space 1}   -1.54{col 65}{space 3}0.124{col 73}{space 4}-.3776931{col 86}{space 3} .0454333
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0875001{col 45}{space 2} .1070706{col 56}{space 1}   -0.82{col 65}{space 3}0.414{col 73}{space 4}-.2975484{col 86}{space 3} .1225482
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1033959{col 45}{space 2} .1084668{col 56}{space 1}   -0.95{col 65}{space 3}0.341{col 73}{space 4}-.3161832{col 86}{space 3} .1093914
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0033695{col 45}{space 2} .0596457{col 56}{space 1}    0.06{col 65}{space 3}0.955{col 73}{space 4}-.1136417{col 86}{space 3} .1203808
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1291564{col 45}{space 2} .0580572{col 56}{space 1}   -2.22{col 65}{space 3}0.026{col 73}{space 4}-.2430516{col 86}{space 3}-.0152613
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} -.178349{col 45}{space 2} .0643775{col 56}{space 1}   -2.77{col 65}{space 3}0.006{col 73}{space 4}-.3046432{col 86}{space 3}-.0520549
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2205494{col 45}{space 2} .0598171{col 56}{space 1}   -3.69{col 65}{space 3}0.000{col 73}{space 4} -.337897{col 86}{space 3}-.1032019
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3846467{col 45}{space 2} .0678911{col 56}{space 1}   -5.67{col 65}{space 3}0.000{col 73}{space 4}-.5178336{col 86}{space 3}-.2514597
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2415861{col 45}{space 2} .0637553{col 56}{space 1}   -3.79{col 65}{space 3}0.000{col 73}{space 4}-.3666595{col 86}{space 3}-.1165126
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0226734{col 45}{space 2} .0689708{col 56}{space 1}   -0.33{col 65}{space 3}0.742{col 73}{space 4}-.1579785{col 86}{space 3} .1126316
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2286187{col 45}{space 2} .0725652{col 56}{space 1}   -3.15{col 65}{space 3}0.002{col 73}{space 4}-.3709752{col 86}{space 3}-.0862623
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1856912{col 45}{space 2} .0777969{col 56}{space 1}   -2.39{col 65}{space 3}0.017{col 73}{space 4}-.3383112{col 86}{space 3}-.0330712
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3649967{col 45}{space 2} .0540274{col 56}{space 1}    6.76{col 65}{space 3}0.000{col 73}{space 4} .2590073{col 86}{space 3} .4709862
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0635752{col 45}{space 2} .0685943{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.1981417{col 86}{space 3} .0709913
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0021085{col 45}{space 2} .0709689{col 56}{space 1}    0.03{col 65}{space 3}0.976{col 73}{space 4}-.1371164{col 86}{space 3} .1413334
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0432351{col 45}{space 2} .0712294{col 56}{space 1}    0.61{col 65}{space 3}0.544{col 73}{space 4}-.0965009{col 86}{space 3} .1829711
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4435767{col 45}{space 2} .0482151{col 56}{space 1}   -9.20{col 65}{space 3}0.000{col 73}{space 4}-.5381638{col 86}{space 3}-.3489896
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0822272{col 45}{space 2} .0544457{col 56}{space 1}   -1.51{col 65}{space 3}0.131{col 73}{space 4}-.1890373{col 86}{space 3}  .024583
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1502587{col 45}{space 2} .0611434{col 56}{space 1}    2.46{col 65}{space 3}0.014{col 73}{space 4} .0303092{col 86}{space 3} .2702083
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.032892{col 45}{space 2} .0721875{col 56}{space 1}   -0.46{col 65}{space 3}0.649{col 73}{space 4}-.1745075{col 86}{space 3} .1087235
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3992227{col 45}{space 2} .0472507{col 56}{space 1}   -8.45{col 65}{space 3}0.000{col 73}{space 4}-.4919179{col 86}{space 3}-.3065274
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1322366{col 45}{space 2}   .06634{col 56}{space 1}    1.99{col 65}{space 3}0.046{col 73}{space 4} .0020926{col 86}{space 3} .2623806
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2071578{col 45}{space 2} .0911346{col 56}{space 1}   -2.27{col 65}{space 3}0.023{col 73}{space 4}-.3859432{col 86}{space 3}-.0283724
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1208546{col 45}{space 2}  .089043{col 56}{space 1}   -1.36{col 65}{space 3}0.175{col 73}{space 4}-.2955369{col 86}{space 3} .0538276
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0737973{col 45}{space 2}  .106031{col 56}{space 1}   -0.70{col 65}{space 3}0.487{col 73}{space 4}-.2818061{col 86}{space 3} .1342115
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2558526{col 45}{space 2} .0872685{col 56}{space 1}    2.93{col 65}{space 3}0.003{col 73}{space 4} .0846515{col 86}{space 3} .4270537
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1292538{col 45}{space 2} .1152942{col 56}{space 1}    1.12{col 65}{space 3}0.262{col 73}{space 4}-.0969273{col 86}{space 3}  .355435
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9234004{col 45}{space 2} .1457423{col 56}{space 1}    6.34{col 65}{space 3}0.000{col 73}{space 4}  .637487{col 86}{space 3} 1.209314
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. estadd local  FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. * Make table 
. esttab pp_nocontrols pp_fe pp_controls pp_fe_controls using 03_tables/table5.tex, tex se replace keep(pp_dummy) coeflabels (pp_dummy "PP voter (dummy)") nomtitles star(* 0.10 ** 0.05 *** 0.01) s(Controls FE, label("Controls" "Region fixed effects")) addnotes("Standard errors are robust" "The outcome variable is a dummy for whether each respondent used a private" "voting booth to cast their vote in the general election of November 2019" "Models 2 and 4 include controls for income, education, age, age squared, size of" "respondent's municipality, and a dummy for respondents identifying as female") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/table5.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/table6.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Generate interaction
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
{txt}(2,957 missing values generated)

{com}. 
. * Run analyses
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy, r

{txt}Linear regression                               Number of obs     = {res}     1,847
                                                {txt}F(3, 1843)        =  {res}     2.18
                                                {txt}Prob > F          = {res}    0.0890
                                                {txt}R-squared         = {res}    0.0049
                                                {txt}Root MSE          =    {res} .30267

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0093021{col 33}{space 2} .0150025{col 44}{space 1}   -0.62{col 53}{space 3}0.535{col 61}{space 4}-.0387258{col 74}{space 3} .0201216
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0258144{col 33}{space 2} .0264424{col 44}{space 1}   -0.98{col 53}{space 3}0.329{col 61}{space 4}-.0776746{col 74}{space 3} .0260458
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1056928{col 33}{space 2} .0430507{col 44}{space 1}    2.46{col 53}{space 3}0.014{col 61}{space 4} .0212595{col 74}{space 3} .1901261
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1020856{col 33}{space 2} .0100418{col 44}{space 1}   10.17{col 53}{space 3}0.000{col 61}{space 4} .0823911{col 74}{space 3} .1217801
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_nocontrols
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. estadd local FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,847
                                                {txt}F(21, 1825)       =  {res}     3.70
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0376
                                                {txt}Root MSE          =    {res} .29912

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                uncomfortable{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}cabine_use {c |}{col 31}{res}{space 2}-.0137941{col 43}{space 2} .0163418{col 54}{space 1}   -0.84{col 63}{space 3}0.399{col 71}{space 4}-.0458448{col 84}{space 3} .0182566
{txt}{space 21}pp_dummy {c |}{col 31}{res}{space 2}-.0370522{col 43}{space 2} .0270462{col 54}{space 1}   -1.37{col 63}{space 3}0.171{col 71}{space 4}-.0900969{col 84}{space 3} .0159926
{txt}{space 10}cabine_use_pp_dummy {c |}{col 31}{res}{space 2} .1051536{col 43}{space 2} .0422713{col 54}{space 1}    2.49{col 63}{space 3}0.013{col 71}{space 4} .0222485{col 84}{space 3} .1880588
{txt}{space 29} {c |}
{space 25}CCAA {c |}
{space 22}Aragón  {c |}{col 31}{res}{space 2}-.0284776{col 43}{space 2} .0389599{col 54}{space 1}   -0.73{col 63}{space 3}0.465{col 71}{space 4}-.1048884{col 84}{space 3} .0479331
{txt}{space 4}Asturias (Principado de)  {c |}{col 31}{res}{space 2} .0876985{col 43}{space 2} .0553588{col 54}{space 1}    1.58{col 63}{space 3}0.113{col 71}{space 4}-.0208747{col 84}{space 3} .1962717
{txt}{space 13}Balears (Illes)  {c |}{col 31}{res}{space 2}  .007329{col 43}{space 2} .0424858{col 54}{space 1}    0.17{col 63}{space 3}0.863{col 71}{space 4}-.0759969{col 84}{space 3}  .090655
{txt}{space 20}Canarias  {c |}{col 31}{res}{space 2}-.0573965{col 43}{space 2} .0389692{col 54}{space 1}   -1.47{col 63}{space 3}0.141{col 71}{space 4}-.1338253{col 84}{space 3} .0190324
{txt}{space 19}Cantabria  {c |}{col 31}{res}{space 2}-.0320745{col 43}{space 2}  .037469{col 54}{space 1}   -0.86{col 63}{space 3}0.392{col 71}{space 4}-.1055612{col 84}{space 3} .0414122
{txt}{space 10}Castilla-La Mancha  {c |}{col 31}{res}{space 2} .1265929{col 43}{space 2} .0577189{col 54}{space 1}    2.19{col 63}{space 3}0.028{col 71}{space 4} .0133908{col 84}{space 3} .2397949
{txt}{space 13}Castilla y León  {c |}{col 31}{res}{space 2} .0904875{col 43}{space 2} .0509775{col 54}{space 1}    1.78{col 63}{space 3}0.076{col 71}{space 4}-.0094928{col 84}{space 3} .1904678
{txt}{space 20}Cataluña  {c |}{col 31}{res}{space 2}-.0579057{col 43}{space 2} .0258834{col 54}{space 1}   -2.24{col 63}{space 3}0.025{col 71}{space 4}  -.10867{col 84}{space 3}-.0071415
{txt}{space 8}Comunitat Valenciana  {c |}{col 31}{res}{space 2} -.086384{col 43}{space 2} .0249477{col 54}{space 1}   -3.46{col 63}{space 3}0.001{col 71}{space 4}-.1353131{col 84}{space 3}-.0374549
{txt}{space 17}Extremadura  {c |}{col 31}{res}{space 2}-.0284337{col 43}{space 2}  .040444{col 54}{space 1}   -0.70{col 63}{space 3}0.482{col 71}{space 4}-.1077552{col 84}{space 3} .0508877
{txt}{space 21}Galicia  {c |}{col 31}{res}{space 2}-.0552346{col 43}{space 2} .0328336{col 54}{space 1}   -1.68{col 63}{space 3}0.093{col 71}{space 4}-.1196299{col 84}{space 3} .0091608
{txt}{space 7}Madrid (Comunidad de)  {c |}{col 31}{res}{space 2}   -.0034{col 43}{space 2} .0298429{col 54}{space 1}   -0.11{col 63}{space 3}0.909{col 71}{space 4}-.0619298{col 84}{space 3} .0551298
{txt}{space 10}Murcia (Región de)  {c |}{col 31}{res}{space 2}-.1102939{col 43}{space 2}  .023943{col 54}{space 1}   -4.61{col 63}{space 3}0.000{col 71}{space 4}-.1572524{col 84}{space 3}-.0633353
{txt}Navarra (Comunidad Foral de)  {c |}{col 31}{res}{space 2} .0287113{col 43}{space 2} .0589705{col 54}{space 1}    0.49{col 63}{space 3}0.626{col 71}{space 4}-.0869455{col 84}{space 3} .1443682
{txt}{space 18}País Vasco  {c |}{col 31}{res}{space 2}-.0854341{col 43}{space 2} .0310725{col 54}{space 1}   -2.75{col 63}{space 3}0.006{col 71}{space 4}-.1463756{col 84}{space 3}-.0244926
{txt}{space 18}Rioja (La)  {c |}{col 31}{res}{space 2} -.040114{col 43}{space 2} .0402575{col 54}{space 1}   -1.00{col 63}{space 3}0.319{col 71}{space 4}-.1190697{col 84}{space 3} .0388417
{txt}{space 2}Ceuta (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .0447056{col 43}{space 2} .0664893{col 54}{space 1}    0.67{col 63}{space 3}0.501{col 71}{space 4}-.0856976{col 84}{space 3} .1751087
{txt}Melilla (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2}  -.07021{col 43}{space 2} .0622005{col 54}{space 1}   -1.13{col 63}{space 3}0.259{col 71}{space 4}-.1922016{col 84}{space 3} .0517815
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .1249262{col 43}{space 2} .0218889{col 54}{space 1}    5.71{col 63}{space 3}0.000{col 71}{space 4} .0819964{col 84}{space 3} .1678561
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_fe
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. estadd local FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.TAMUNI age age_sq i.education, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(27, 1328)       =  {res}     2.86
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0367
                                                {txt}Root MSE          =    {res} .28379

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0337134{col 45}{space 2}  .016701{col 56}{space 1}   -2.02{col 65}{space 3}0.044{col 73}{space 4}-.0664767{col 86}{space 3}-.0009501
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0365706{col 45}{space 2} .0297247{col 56}{space 1}   -1.23{col 65}{space 3}0.219{col 73}{space 4}-.0948831{col 86}{space 3}  .021742
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1175523{col 45}{space 2} .0479617{col 56}{space 1}    2.45{col 65}{space 3}0.014{col 73}{space 4} .0234633{col 86}{space 3} .2116413
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0290122{col 45}{space 2} .0159768{col 56}{space 1}    1.82{col 65}{space 3}0.070{col 73}{space 4}-.0023303{col 86}{space 3} .0603548
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0298092{col 45}{space 2} .0634945{col 56}{space 1}    0.47{col 65}{space 3}0.639{col 73}{space 4}-.0947513{col 86}{space 3} .1543697
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0679181{col 45}{space 2} .0413665{col 56}{space 1}    1.64{col 65}{space 3}0.101{col 73}{space 4}-.0132327{col 86}{space 3}  .149069
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0057013{col 45}{space 2} .0306162{col 56}{space 1}    0.19{col 65}{space 3}0.852{col 73}{space 4}-.0543601{col 86}{space 3} .0657626
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0134649{col 45}{space 2} .0291278{col 56}{space 1}    0.46{col 65}{space 3}0.644{col 73}{space 4}-.0436767{col 86}{space 3} .0706064
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0116287{col 45}{space 2} .0276334{col 56}{space 1}    0.42{col 65}{space 3}0.674{col 73}{space 4}-.0425811{col 86}{space 3} .0658385
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0367435{col 45}{space 2} .0289269{col 56}{space 1}   -1.27{col 65}{space 3}0.204{col 73}{space 4} -.093491{col 86}{space 3} .0200039
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0149316{col 45}{space 2} .0425222{col 56}{space 1}   -0.35{col 65}{space 3}0.726{col 73}{space 4}-.0983496{col 86}{space 3} .0684864
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0666733{col 45}{space 2} .0706049{col 56}{space 1}    0.94{col 65}{space 3}0.345{col 73}{space 4}-.0718361{col 86}{space 3} .2051826
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0853735{col 45}{space 2} .0336113{col 56}{space 1}   -2.54{col 65}{space 3}0.011{col 73}{space 4}-.1513105{col 86}{space 3}-.0194365
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}    -.073{col 45}{space 2} .0327401{col 56}{space 1}   -2.23{col 65}{space 3}0.026{col 73}{space 4}-.1372279{col 86}{space 3}-.0087721
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0599538{col 45}{space 2} .0376189{col 56}{space 1}    1.59{col 65}{space 3}0.111{col 73}{space 4}-.0138451{col 86}{space 3} .1337528
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0172546{col 45}{space 2} .0325386{col 56}{space 1}    0.53{col 65}{space 3}0.596{col 73}{space 4}-.0465781{col 86}{space 3} .0810873
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .036592{col 45}{space 2} .0366081{col 56}{space 1}    1.00{col 65}{space 3}0.318{col 73}{space 4} -.035224{col 86}{space 3} .1084081
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0035241{col 45}{space 2} .0329026{col 56}{space 1}    0.11{col 65}{space 3}0.915{col 73}{space 4}-.0610226{col 86}{space 3} .0680708
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0506184{col 45}{space 2} .0321956{col 56}{space 1}   -1.57{col 65}{space 3}0.116{col 73}{space 4}-.1137782{col 86}{space 3} .0125414
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0459084{col 45}{space 2} .0362575{col 56}{space 1}   -1.27{col 65}{space 3}0.206{col 73}{space 4}-.1170366{col 86}{space 3} .0252198
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0021341{col 45}{space 2} .0031694{col 56}{space 1}   -0.67{col 65}{space 3}0.501{col 73}{space 4}-.0083518{col 86}{space 3} .0040835
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000251{col 45}{space 2} .0000336{col 56}{space 1}    0.75{col 65}{space 3}0.454{col 73}{space 4}-.0000407{col 86}{space 3} .0000909
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0870528{col 45}{space 2} .0905141{col 56}{space 1}   -0.96{col 65}{space 3}0.336{col 73}{space 4} -.264619{col 86}{space 3} .0905134
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0517586{col 45}{space 2} .0917094{col 56}{space 1}   -0.56{col 65}{space 3}0.573{col 73}{space 4}-.2316697{col 86}{space 3} .1281524
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0982894{col 45}{space 2} .0920835{col 56}{space 1}   -1.07{col 65}{space 3}0.286{col 73}{space 4}-.2789343{col 86}{space 3} .0823555
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0911509{col 45}{space 2} .0916408{col 56}{space 1}   -0.99{col 65}{space 3}0.320{col 73}{space 4}-.2709273{col 86}{space 3} .0886256
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0850111{col 45}{space 2} .0919742{col 56}{space 1}   -0.92{col 65}{space 3}0.356{col 73}{space 4}-.2654417{col 86}{space 3} .0954196
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1876158{col 45}{space 2} .1073685{col 56}{space 1}    1.75{col 65}{space 3}0.081{col 73}{space 4}-.0230146{col 86}{space 3} .3982461
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. estadd local FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.TAMUNI age age_sq i.education i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(45, 1310)       =  {res}     2.31
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0768
                                                {txt}Root MSE          =    {res} .27971

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0161885{col 45}{space 2} .0174219{col 56}{space 1}   -0.93{col 65}{space 3}0.353{col 73}{space 4}-.0503663{col 86}{space 3} .0179893
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0391079{col 45}{space 2} .0296057{col 56}{space 1}   -1.32{col 65}{space 3}0.187{col 73}{space 4}-.0971876{col 86}{space 3} .0189718
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1070496{col 45}{space 2} .0459618{col 56}{space 1}    2.33{col 65}{space 3}0.020{col 73}{space 4} .0168827{col 86}{space 3} .1972165
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0286614{col 45}{space 2} .0157818{col 56}{space 1}    1.82{col 65}{space 3}0.070{col 73}{space 4}-.0022989{col 86}{space 3} .0596217
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0252418{col 45}{space 2} .0637596{col 56}{space 1}    0.40{col 65}{space 3}0.692{col 73}{space 4}-.0998403{col 86}{space 3}  .150324
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0809688{col 45}{space 2} .0406164{col 56}{space 1}    1.99{col 65}{space 3}0.046{col 73}{space 4} .0012885{col 86}{space 3} .1606491
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0097233{col 45}{space 2} .0303799{col 56}{space 1}    0.32{col 65}{space 3}0.749{col 73}{space 4}-.0498753{col 86}{space 3}  .069322
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0111537{col 45}{space 2} .0281572{col 56}{space 1}    0.40{col 65}{space 3}0.692{col 73}{space 4}-.0440845{col 86}{space 3} .0663919
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0064156{col 45}{space 2} .0278816{col 56}{space 1}    0.23{col 65}{space 3}0.818{col 73}{space 4}-.0482818{col 86}{space 3}  .061113
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0375557{col 45}{space 2} .0301565{col 56}{space 1}   -1.25{col 65}{space 3}0.213{col 73}{space 4}-.0967161{col 86}{space 3} .0216047
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0266351{col 45}{space 2} .0424242{col 56}{space 1}   -0.63{col 65}{space 3}0.530{col 73}{space 4}-.1098619{col 86}{space 3} .0565918
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0615274{col 45}{space 2}  .067269{col 56}{space 1}    0.91{col 65}{space 3}0.361{col 73}{space 4}-.0704392{col 86}{space 3} .1934941
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0770483{col 45}{space 2} .0470606{col 56}{space 1}   -1.64{col 65}{space 3}0.102{col 73}{space 4}-.1693707{col 86}{space 3} .0152742
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.075425{col 45}{space 2} .0420327{col 56}{space 1}   -1.79{col 65}{space 3}0.073{col 73}{space 4}-.1578838{col 86}{space 3} .0070338
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0546482{col 45}{space 2} .0370362{col 56}{space 1}    1.48{col 65}{space 3}0.140{col 73}{space 4}-.0180085{col 86}{space 3} .1273049
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0194887{col 45}{space 2}    .0327{col 56}{space 1}    0.60{col 65}{space 3}0.551{col 73}{space 4}-.0446615{col 86}{space 3} .0836388
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0053875{col 45}{space 2}  .037727{col 56}{space 1}    0.14{col 65}{space 3}0.886{col 73}{space 4}-.0686244{col 86}{space 3} .0793994
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}  -.00761{col 45}{space 2} .0338595{col 56}{space 1}   -0.22{col 65}{space 3}0.822{col 73}{space 4}-.0740347{col 86}{space 3} .0588147
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0393001{col 45}{space 2} .0361273{col 56}{space 1}   -1.09{col 65}{space 3}0.277{col 73}{space 4}-.1101737{col 86}{space 3} .0315735
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1047177{col 45}{space 2} .0427722{col 56}{space 1}   -2.45{col 65}{space 3}0.014{col 73}{space 4}-.1886272{col 86}{space 3}-.0208082
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0011097{col 45}{space 2} .0031349{col 56}{space 1}   -0.35{col 65}{space 3}0.723{col 73}{space 4}-.0072596{col 86}{space 3} .0050402
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000159{col 45}{space 2} .0000332{col 56}{space 1}    0.48{col 65}{space 3}0.633{col 73}{space 4}-.0000493{col 86}{space 3}  .000081
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0806284{col 45}{space 2} .0923209{col 56}{space 1}   -0.87{col 65}{space 3}0.383{col 73}{space 4}-.2617413{col 86}{space 3} .1004846
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0439123{col 45}{space 2} .0945747{col 56}{space 1}   -0.46{col 65}{space 3}0.643{col 73}{space 4}-.2294467{col 86}{space 3}  .141622
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0905356{col 45}{space 2} .0949785{col 56}{space 1}   -0.95{col 65}{space 3}0.341{col 73}{space 4}-.2768623{col 86}{space 3}  .095791
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0804828{col 45}{space 2} .0944429{col 56}{space 1}   -0.85{col 65}{space 3}0.394{col 73}{space 4}-.2657586{col 86}{space 3} .1047931
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0753385{col 45}{space 2} .0950458{col 56}{space 1}   -0.79{col 65}{space 3}0.428{col 73}{space 4}-.2617972{col 86}{space 3} .1111201
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} -.022042{col 45}{space 2} .0356966{col 56}{space 1}   -0.62{col 65}{space 3}0.537{col 73}{space 4}-.0920707{col 86}{space 3} .0479867
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0561672{col 45}{space 2} .0542064{col 56}{space 1}    1.04{col 65}{space 3}0.300{col 73}{space 4}-.0501736{col 86}{space 3}  .162508
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0525638{col 45}{space 2} .0516608{col 56}{space 1}    1.02{col 65}{space 3}0.309{col 73}{space 4}-.0487832{col 86}{space 3} .1539107
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0624198{col 45}{space 2} .0343576{col 56}{space 1}   -1.82{col 65}{space 3}0.069{col 73}{space 4}-.1298216{col 86}{space 3} .0049821
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0356421{col 45}{space 2} .0365304{col 56}{space 1}   -0.98{col 65}{space 3}0.329{col 73}{space 4}-.1073065{col 86}{space 3} .0360222
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1264314{col 45}{space 2} .0597288{col 56}{space 1}    2.12{col 65}{space 3}0.034{col 73}{space 4} .0092569{col 86}{space 3} .2436059
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0845255{col 45}{space 2} .0553489{col 56}{space 1}    1.53{col 65}{space 3}0.127{col 73}{space 4}-.0240567{col 86}{space 3} .1931077
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0088615{col 45}{space 2} .0351612{col 56}{space 1}    0.25{col 65}{space 3}0.801{col 73}{space 4}-.0601169{col 86}{space 3} .0778398
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0548639{col 45}{space 2} .0275883{col 56}{space 1}   -1.99{col 65}{space 3}0.047{col 73}{space 4} -.108986{col 86}{space 3}-.0007418
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0206756{col 45}{space 2} .0432684{col 56}{space 1}   -0.48{col 65}{space 3}0.633{col 73}{space 4}-.1055586{col 86}{space 3} .0642074
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0932758{col 45}{space 2} .0285169{col 56}{space 1}   -3.27{col 65}{space 3}0.001{col 73}{space 4}-.1492196{col 86}{space 3}-.0373319
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0972986{col 45}{space 2} .0414976{col 56}{space 1}    2.34{col 65}{space 3}0.019{col 73}{space 4} .0158896{col 86}{space 3} .1787075
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0643376{col 45}{space 2} .0246891{col 56}{space 1}   -2.61{col 65}{space 3}0.009{col 73}{space 4}-.1127721{col 86}{space 3} -.015903
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0161522{col 45}{space 2} .0558138{col 56}{space 1}   -0.29{col 65}{space 3}0.772{col 73}{space 4}-.1256463{col 86}{space 3} .0933419
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0604004{col 45}{space 2} .0362028{col 56}{space 1}   -1.67{col 65}{space 3}0.095{col 73}{space 4}-.1314222{col 86}{space 3} .0106213
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0909534{col 45}{space 2} .0257658{col 56}{space 1}   -3.53{col 65}{space 3}0.000{col 73}{space 4}-.1415002{col 86}{space 3}-.0404066
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0927365{col 45}{space 2} .0812046{col 56}{space 1}    1.14{col 65}{space 3}0.254{col 73}{space 4}-.0665686{col 86}{space 3} .2520417
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0324908{col 45}{space 2} .0644684{col 56}{space 1}   -0.50{col 65}{space 3}0.614{col 73}{space 4}-.1589634{col 86}{space 3} .0939819
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1535666{col 45}{space 2} .1106493{col 56}{space 1}    1.39{col 65}{space 3}0.165{col 73}{space 4}-.0635025{col 86}{space 3} .3706358
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_fe_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. estadd local FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. * Make table
. esttab uncomf_nocontrols uncomf_controls uncomf_fe uncomf_fe_controls using 03_tables/table6.tex, tex se replace  keep (cabine_use pp_dummy cabine_use_pp_dummy) coeflabels (cabine_use "Used a booth to vote" pp_dummy "Voted for PP" cabine_use_pp_dummy "Used booth x voted PP") star(* 0.10 ** 0.05 *** 0.01) s(Controls FE, label("Controls" "Region fixed effects")) nomtitles addnotes("Standard errors are robust" "The outcome variable is a dummy for whether each respondent showed" "signs of discomfort during the survey interview" "Models 2 and 4 include controls for income, education, age, age squared, size of" "respondent's municipality, and a dummy for respondents identifying as female") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/table6.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. * Run analyses
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & (turnout_above_median_p3 == 1 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32160 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,418
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59208{txt}){col 67}= {res}  10641.95
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8748
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4046
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,209{txt}{col 51}Root MSE{col 67}= {res}    5.2288

{txt}{ralign 84:(Std. err. adjusted for {res:59,209} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.121899{col 32}{space 2}  .062844{col 43}{space 1}  -97.41{col 52}{space 3}0.000{col 60}{space 4}-6.245074{col 73}{space 3}-5.998725
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0404565{col 32}{space 2} .0712617{col 43}{space 1}    0.57{col 52}{space 3}0.570{col 60}{space 4}-.0992168{col 73}{space 3} .1801298
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4519787{col 32}{space 2} .8647178{col 43}{space 1}    0.52{col 52}{space 3}0.601{col 60}{space 4}-1.242872{col 73}{space 3} 2.146829
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-4.487034{col 32}{space 2} 1.060013{col 43}{space 1}   -4.23{col 52}{space 3}0.000{col 60}{space 4}-6.564663{col 73}{space 3}-2.409405
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.43796{col 32}{space 2} .0151946{col 43}{space 1} 1805.77{col 52}{space 3}0.000{col 60}{space 4} 27.40818{col 73}{space 3} 27.46774
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59209{col 38}{space 1}    59209{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_hte_turnout_1
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & (turnout_above_median_p3 == 0 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32160 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,418
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59208{txt}){col 67}= {res}  10571.22
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4044
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,209{txt}{col 51}Root MSE{col 67}= {res}    5.2291

{txt}{ralign 84:(Std. err. adjusted for {res:59,209} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.121899{col 32}{space 2}  .062844{col 43}{space 1}  -97.41{col 52}{space 3}0.000{col 60}{space 4}-6.245074{col 73}{space 3}-5.998725
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0404565{col 32}{space 2} .0712617{col 43}{space 1}    0.57{col 52}{space 3}0.570{col 60}{space 4}-.0992168{col 73}{space 3} .1801298
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.883993{col 32}{space 2} 1.045991{col 43}{space 1}    1.80{col 52}{space 3}0.072{col 60}{space 4}-.1661532{col 73}{space 3}  3.93414
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -1.80488{col 32}{space 2} 1.795387{col 43}{space 1}   -1.01{col 52}{space 3}0.315{col 60}{space 4}-5.323845{col 73}{space 3} 1.714086
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.43593{col 32}{space 2} .0151956{col 43}{space 1} 1805.52{col 52}{space 3}0.000{col 60}{space 4} 27.40615{col 73}{space 3} 27.46572
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59209{col 38}{space 1}    59209{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_hte_turnout_2
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella if (turnout_above_median_p3 == 1 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,902
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  76129{txt}){col 67}= {res}  45154.40
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8201
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7137
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4234
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,130{txt}{col 51}Root MSE{col 67}= {res}    9.4296

{txt}{ralign 84:(Std. err. adjusted for {res:76,130} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.92846{col 32}{space 2} .0686972{col 43}{space 1} -188.19{col 52}{space 3}0.000{col 60}{space 4} -13.0631{col 73}{space 3}-12.79381
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.027174{col 32}{space 2} .0779292{col 43}{space 1}  -13.18{col 52}{space 3}0.000{col 60}{space 4}-1.179914{col 73}{space 3}-.8744326
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3717993{col 32}{space 2} .7393254{col 43}{space 1}    0.50{col 52}{space 3}0.615{col 60}{space 4}-1.077275{col 73}{space 3} 1.820873
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.767779{col 32}{space 2} .9162231{col 43}{space 1}   -4.11{col 52}{space 3}0.000{col 60}{space 4}-5.563572{col 73}{space 3}-1.971986
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.61964{col 32}{space 2} .0115182{col 43}{space 1} 3005.63{col 52}{space 3}0.000{col 60}{space 4} 34.59706{col 73}{space 3} 34.64221
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76130{col 38}{space 1}    76130{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_hte_turnout_3
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella if (turnout_above_median_p3 == 0 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,902
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  76129{txt}){col 67}= {res}  44895.70
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8201
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7137
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4233
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,130{txt}{col 51}Root MSE{col 67}= {res}    9.4302

{txt}{ralign 84:(Std. err. adjusted for {res:76,130} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.92846{col 32}{space 2} .0686972{col 43}{space 1} -188.19{col 52}{space 3}0.000{col 60}{space 4} -13.0631{col 73}{space 3}-12.79381
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.027174{col 32}{space 2} .0779292{col 43}{space 1}  -13.18{col 52}{space 3}0.000{col 60}{space 4}-1.179914{col 73}{space 3}-.8744326
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4537043{col 32}{space 2} .9129521{col 43}{space 1}    0.50{col 52}{space 3}0.619{col 60}{space 4}-1.335677{col 73}{space 3} 2.243086
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-1.140525{col 32}{space 2} 1.718505{col 43}{space 1}   -0.66{col 52}{space 3}0.507{col 60}{space 4}-4.508786{col 73}{space 3} 2.227737
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.61844{col 32}{space 2} .0115187{col 43}{space 1} 3005.42{col 52}{space 3}0.000{col 60}{space 4} 34.59587{col 73}{space 3} 34.64102
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76130{col 38}{space 1}    76130{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_hte_turnout_4
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella i.period  if (turnout_above_median_p3 == 1 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,902
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  76129{txt}){col 67}= {res}  52277.36
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9147
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8643
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7266
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,130{txt}{col 51}Root MSE{col 67}= {res}    6.4927

{txt}{ralign 84:(Std. err. adjusted for {res:76,130} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.32767{col 32}{space 2} .0738545{col 43}{space 1} -275.24{col 52}{space 3}0.000{col 60}{space 4}-20.47242{col 73}{space 3}-20.18291
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2105625{col 32}{space 2} .0751799{col 43}{space 1}    2.80{col 52}{space 3}0.005{col 60}{space 4} .0632103{col 73}{space 3} .3579147
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7514515{col 32}{space 2} .7391676{col 43}{space 1}    1.02{col 52}{space 3}0.309{col 60}{space 4}-.6973134{col 73}{space 3} 2.200216
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-5.005515{col 32}{space 2} .9160036{col 43}{space 1}   -5.46{col 52}{space 3}0.000{col 60}{space 4}-6.800878{col 73}{space 3}-3.210152
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.03912{col 32}{space 2} .0365262{col 43}{space 1} -384.36{col 52}{space 3}0.000{col 60}{space 4}-14.11071{col 73}{space 3}-13.96753
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.22982{col 32}{space 2} .0235982{col 43}{space 1} 1747.16{col 52}{space 3}0.000{col 60}{space 4} 41.18356{col 73}{space 3} 41.27607
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76130{col 38}{space 1}    76130{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_hte_turnout_5
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella i.period  if (turnout_above_median_p3 == 0 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,902
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  76129{txt}){col 67}= {res}  52080.32
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9147
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8643
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7266
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,130{txt}{col 51}Root MSE{col 67}= {res}    6.4929

{txt}{ralign 84:(Std. err. adjusted for {res:76,130} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.32833{col 32}{space 2} .0738546{col 43}{space 1} -275.25{col 52}{space 3}0.000{col 60}{space 4}-20.47309{col 73}{space 3}-20.18358
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2106738{col 32}{space 2} .0751799{col 43}{space 1}    2.80{col 52}{space 3}0.005{col 60}{space 4} .0633216{col 73}{space 3}  .358026
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .8333907{col 32}{space 2} .9128248{col 43}{space 1}    0.91{col 52}{space 3}0.361{col 60}{space 4}-.9557416{col 73}{space 3} 2.622523
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.378372{col 32}{space 2} 1.718391{col 43}{space 1}   -1.38{col 52}{space 3}0.166{col 60}{space 4} -5.74641{col 73}{space 3} .9896658
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.04038{col 32}{space 2} .0365271{col 43}{space 1} -384.38{col 52}{space 3}0.000{col 60}{space 4}-14.11197{col 73}{space 3}-13.96879
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.22922{col 32}{space 2} .0235988{col 43}{space 1} 1747.09{col 52}{space 3}0.000{col 60}{space 4} 41.18297{col 73}{space 3} 41.27547
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76130{col 38}{space 1}    76130{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_hte_turnout_6
{txt}
{com}. 
. * Make table
. esttab twoperiods_hte_turnout_1 twoperiods_hte_turnout_2 twoperiods_hte_turnout_3 twoperiods_hte_turnout_4 twoperiods_hte_turnout_5 twoperiods_hte_turnout_6 using 03_tables/tabled1.tex, tex se replace mtitles ("Turnout above median" "Turnout below median" "Turnout above median" "Turnout below median" "Turnout above median" "Turnout below median")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 2.period "2014-2015 election" d1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep "EP election in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled1.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled2.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & CODCCAA < 18, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32013 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   117,934
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  58966{txt}){col 67}= {res}  10521.44
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4036
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    58,967{txt}{col 51}Root MSE{col 67}= {res}    5.2178

{txt}{ralign 84:(Std. err. adjusted for {res:58,967} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.083933{col 32}{space 2}  .063095{col 43}{space 1}  -96.42{col 52}{space 3}0.000{col 60}{space 4}  -6.2076{col 73}{space 3}-5.960267
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0207659{col 32}{space 2}  .071462{col 43}{space 1}    0.29{col 52}{space 3}0.771{col 60}{space 4}-.1193001{col 73}{space 3} .1608318
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  1.13002{col 32}{space 2} .6933797{col 43}{space 1}    1.63{col 52}{space 3}0.103{col 60}{space 4}-.2290071{col 73}{space 3} 2.489047
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.126266{col 32}{space 2} 1.121951{col 43}{space 1}   -2.79{col 52}{space 3}0.005{col 60}{space 4}-5.325296{col 73}{space 3}-.9272369
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.36519{col 32}{space 2} .0151938{col 43}{space 1} 1801.08{col 52}{space 3}0.000{col 60}{space 4} 27.33541{col 73}{space 3} 27.39497
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    58967{col 38}{space 1}    58967{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_pp_ddd_excl
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella if CODCCAA < 18, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26189 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,069
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  75814{txt}){col 67}= {res}  44847.65
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8197
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7131
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4227
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,815{txt}{col 51}Root MSE{col 67}= {res}    9.4245

{txt}{ralign 84:(Std. err. adjusted for {res:75,815} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} -12.8905{col 32}{space 2} .0689574{col 43}{space 1} -186.93{col 52}{space 3}0.000{col 60}{space 4}-13.02566{col 73}{space 3}-12.75534
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.042796{col 32}{space 2} .0781473{col 43}{space 1}  -13.34{col 52}{space 3}0.000{col 60}{space 4}-1.195964{col 73}{space 3}-.8896278
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .374794{col 32}{space 2} .5894712{col 43}{space 1}    0.64{col 52}{space 3}0.525{col 60}{space 4}-.7805667{col 73}{space 3} 1.530155
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.438529{col 32}{space 2} 1.008388{col 43}{space 1}   -2.42{col 52}{space 3}0.016{col 60}{space 4}-4.414964{col 73}{space 3}-.4620944
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.54986{col 32}{space 2} .0115196{col 43}{space 1} 2999.22{col 52}{space 3}0.000{col 60}{space 4} 34.52728{col 73}{space 3} 34.57244
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75815{col 38}{space 1}    75815{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_pp_ddd_excl
{txt}
{com}. 
. reghdfe pp_voteshare post##ep##ciutadella i.period if CODCCAA < 18, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26189 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,069
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  75814{txt}){col 67}= {res}  51952.90
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9146
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8641
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7265
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,815{txt}{col 51}Root MSE{col 67}= {res}    6.4869

{txt}{ralign 84:(Std. err. adjusted for {res:75,815} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.28726{col 32}{space 2} .0741108{col 43}{space 1} -273.74{col 52}{space 3}0.000{col 60}{space 4}-20.43251{col 73}{space 3}  -20.142
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1933874{col 32}{space 2} .0753874{col 43}{space 1}    2.57{col 52}{space 3}0.010{col 60}{space 4} .0456285{col 73}{space 3} .3411463
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7536715{col 32}{space 2} .5892698{col 43}{space 1}    1.28{col 52}{space 3}0.201{col 60}{space 4}-.4012946{col 73}{space 3} 1.908638
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.674713{col 32}{space 2} 1.008184{col 43}{space 1}   -3.64{col 52}{space 3}0.000{col 60}{space 4}-5.650749{col 73}{space 3}-1.698676
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.03575{col 32}{space 2} .0366123{col 43}{space 1} -383.36{col 52}{space 3}0.000{col 60}{space 4}-14.10751{col 73}{space 3}  -13.964
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.15768{col 32}{space 2}  .023637{col 43}{space 1} 1741.24{col 52}{space 3}0.000{col 60}{space 4} 41.11135{col 73}{space 3} 41.20401
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75815{col 38}{space 1}    75815{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_pp_ddd_excl
{txt}
{com}. 
. * Make table
. esttab twoperiods_pp_ddd_excl prepost_pp_ddd_excl threeperiods_pp_ddd_excl using 03_tables/tabled2.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled2.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled3.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_notelecspecific) cluster(mesa_code_notelecspecific)
{res}{txt}(dropped 19422 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   131,212
{txt}Absorbing 1 HDFE group{col 51}F({res}   6{txt},{res}  50410{txt}){col 67}= {res}   6496.27
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9115
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8562
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3122
{txt}{col 1}Number of clusters ({res}mesa_code_notelecspecific{txt}) {col 30}= {res}    50,411{txt}{col 51}Root MSE{col 67}= {res}    5.5233

{txt}{ralign 84:(Std. err. adjusted for {res:50,411} clusters in {res:mesa_code_notelecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-5.961871{col 32}{space 2} .0621343{col 43}{space 1}  -95.95{col 52}{space 3}0.000{col 60}{space 4}-6.083655{col 73}{space 3}-5.840088
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2} .0679477{col 32}{space 2} .0632157{col 43}{space 1}    1.07{col 52}{space 3}0.282{col 60}{space 4}-.0559557{col 73}{space 3} .1918512
{txt}{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1204319{col 32}{space 2} .0666023{col 43}{space 1}   -1.81{col 52}{space 3}0.071{col 60}{space 4}-.2509731{col 73}{space 3} .0101093
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.007958{col 32}{space 2} .6932979{col 43}{space 1}    1.45{col 52}{space 3}0.146{col 60}{space 4}-.3509135{col 73}{space 3}  2.36683
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  1.13959{col 32}{space 2} .6664011{col 43}{space 1}    1.71{col 52}{space 3}0.087{col 60}{space 4}-.1665638{col 73}{space 3} 2.445743
{txt}{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.985068{col 32}{space 2} .7370404{col 43}{space 1}   -4.05{col 52}{space 3}0.000{col 60}{space 4}-4.429676{col 73}{space 3}-1.540461
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.19558{col 32}{space 2} .0476963{col 43}{space 1}  570.18{col 52}{space 3}0.000{col 60}{space 4}  27.1021{col 73}{space 3} 27.28907
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 27}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}               Absorbed FE{col 28}{c |} Categories{col 41} - Redundant{col 53}  = Num. Coefs{col 68}{c |}
{res}{col 1}{text}{hline 27}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_notelecspecific{col 28}{c |}{space 1}    50411{col 41}{space 1}    50411{col 53}{result}{space 1}        0{col 67}{text}*{col 68}{c |}
{res}{col 1}{text}{hline 27}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_ddd_cluster
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_notelecspecific) cluster(mesa_code_notelecspecific)
{res}{txt}(dropped 16098 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   215,191
{txt}Absorbing 1 HDFE group{col 51}F({res}   6{txt},{res}  62043{txt}){col 67}= {res}  26171.86
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8083
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7307
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3932
{txt}{col 1}Number of clusters ({res}mesa_code_notelecspecific{txt}) {col 30}= {res}    62,044{txt}{col 51}Root MSE{col 67}= {res}    9.1796

{txt}{ralign 84:(Std. err. adjusted for {res:62,044} clusters in {res:mesa_code_notelecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.76107{col 32}{space 2}  .067508{col 43}{space 1} -189.03{col 52}{space 3}0.000{col 60}{space 4}-12.89338{col 73}{space 3}-12.62875
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2} 1.696387{col 32}{space 2} .0563313{col 43}{space 1}   30.11{col 52}{space 3}0.000{col 60}{space 4} 1.585978{col 73}{space 3} 1.806797
{txt}{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.106767{col 32}{space 2} .0679963{col 43}{space 1}  -16.28{col 52}{space 3}0.000{col 60}{space 4} -1.24004{col 73}{space 3}-.9734937
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2453592{col 32}{space 2} .5893067{col 43}{space 1}    0.42{col 52}{space 3}0.677{col 60}{space 4}-.9096832{col 73}{space 3} 1.400402
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1130251{col 32}{space 2} .7162968{col 43}{space 1}   -0.16{col 52}{space 3}0.875{col 60}{space 4}-1.516968{col 73}{space 3} 1.290918
{txt}{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.374559{col 32}{space 2} .7799553{col 43}{space 1}   -3.04{col 52}{space 3}0.002{col 60}{space 4}-3.903273{col 73}{space 3}-.8458446
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 33.48393{col 32}{space 2} .0426622{col 43}{space 1}  784.86{col 52}{space 3}0.000{col 60}{space 4} 33.40031{col 73}{space 3} 33.56755
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 27}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}               Absorbed FE{col 28}{c |} Categories{col 41} - Redundant{col 53}  = Num. Coefs{col 68}{c |}
{res}{col 1}{text}{hline 27}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_notelecspecific{col 28}{c |}{space 1}    62044{col 41}{space 1}    62044{col 53}{result}{space 1}        0{col 67}{text}*{col 68}{c |}
{res}{col 1}{text}{hline 27}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_ddd_cluster
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_notelecspecific) cluster(mesa_code_notelecspecific)
{res}{txt}(dropped 16098 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   215,191
{txt}Absorbing 1 HDFE group{col 51}F({res}   7{txt},{res}  62043{txt}){col 67}= {res}  31857.70
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8997
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8591
{txt}{col 51}Within R-sq.{col 67}= {res}    0.6826
{txt}{col 1}Number of clusters ({res}mesa_code_notelecspecific{txt}) {col 30}= {res}    62,044{txt}{col 51}Root MSE{col 67}= {res}    6.6396

{txt}{ralign 84:(Std. err. adjusted for {res:62,044} clusters in {res:mesa_code_notelecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.08696{col 32}{space 2} .0745255{col 43}{space 1} -269.53{col 52}{space 3}0.000{col 60}{space 4}-20.23303{col 73}{space 3}-19.94089
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2} .6974151{col 32}{space 2} .0538649{col 43}{space 1}   12.95{col 52}{space 3}0.000{col 60}{space 4} .5918398{col 73}{space 3} .8029905
{txt}{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.0808449{col 32}{space 2} .0665346{col 43}{space 1}   -1.22{col 52}{space 3}0.224{col 60}{space 4}-.2112529{col 73}{space 3} .0495632
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .5363122{col 32}{space 2}  .589119{col 43}{space 1}    0.91{col 52}{space 3}0.363{col 60}{space 4}-.6183623{col 73}{space 3} 1.690987
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .8859473{col 32}{space 2} .7160947{col 43}{space 1}    1.24{col 52}{space 3}0.216{col 60}{space 4}-.5175999{col 73}{space 3} 2.289494
{txt}{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -3.40048{col 32}{space 2} .7798207{col 43}{space 1}   -4.36{col 52}{space 3}0.000{col 60}{space 4}-4.928931{col 73}{space 3} -1.87203
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.06989{col 32}{space 2} .0392235{col 43}{space 1} -358.71{col 52}{space 3}0.000{col 60}{space 4}-14.14677{col 73}{space 3}-13.99301
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.71148{col 32}{space 2} .0489205{col 43}{space 1}  832.20{col 52}{space 3}0.000{col 60}{space 4} 40.61559{col 73}{space 3} 40.80736
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 27}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}               Absorbed FE{col 28}{c |} Categories{col 41} - Redundant{col 53}  = Num. Coefs{col 68}{c |}
{res}{col 1}{text}{hline 27}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_notelecspecific{col 28}{c |}{space 1}    62044{col 41}{space 1}    62044{col 53}{result}{space 1}        0{col 67}{text}*{col 68}{c |}
{res}{col 1}{text}{hline 27}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_ddd_cluster
{txt}
{com}. 
. * Make table
. esttab twoperiods_ddd_cluster prepost_ddd_cluster threeperiods_ddd_cluster using 03_tables/tabled3.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station fixed effects" "Standard errors are clustered by voting station") 
{res}{txt}(output written to {browse  `"03_tables/tabled3.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled4.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain_2.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32172 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,470
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59234{txt}){col 67}= {res}  10592.53
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4046
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,235{txt}{col 51}Root MSE{col 67}= {res}    5.2282

{txt}{ralign 84:(Std. err. adjusted for {res:59,235} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.121899{col 32}{space 2}  .062844{col 43}{space 1}  -97.41{col 52}{space 3}0.000{col 60}{space 4}-6.245074{col 73}{space 3}-5.998725
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0404565{col 32}{space 2} .0712617{col 43}{space 1}    0.57{col 52}{space 3}0.570{col 60}{space 4}-.0992168{col 73}{space 3} .1801298
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.248487{col 32}{space 2} .6684944{col 43}{space 1}    1.87{col 52}{space 3}0.062{col 60}{space 4} -.061765{col 73}{space 3} 2.558739
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.891406{col 32}{space 2} 1.168785{col 43}{space 1}   -2.47{col 52}{space 3}0.013{col 60}{space 4}-5.182229{col 73}{space 3}-.6005829
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.43679{col 32}{space 2} .0151896{col 43}{space 1} 1806.28{col 52}{space 3}0.000{col 60}{space 4} 27.40702{col 73}{space 3} 27.46656
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59235{col 38}{space 1}    59235{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_tables
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26311 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,988
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  76160{txt}){col 67}= {res}  45015.31
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8200
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7136
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4234
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,161{txt}{col 51}Root MSE{col 67}= {res}    9.4294

{txt}{ralign 84:(Std. err. adjusted for {res:76,161} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.92846{col 32}{space 2} .0686972{col 43}{space 1} -188.19{col 52}{space 3}0.000{col 60}{space 4} -13.0631{col 73}{space 3}-12.79381
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.027174{col 32}{space 2} .0779292{col 43}{space 1}  -13.18{col 52}{space 3}0.000{col 60}{space 4}-1.179914{col 73}{space 3}-.8744326
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .9956336{col 32}{space 2} .5962998{col 43}{space 1}    1.67{col 52}{space 3}0.095{col 60}{space 4} -.173111{col 73}{space 3} 2.164378
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -3.06124{col 32}{space 2} 1.032842{col 43}{space 1}   -2.96{col 52}{space 3}0.003{col 60}{space 4}-5.085605{col 73}{space 3}-1.036875
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.61929{col 32}{space 2} .0115141{col 43}{space 1} 3006.69{col 52}{space 3}0.000{col 60}{space 4} 34.59673{col 73}{space 3} 34.64186
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76161{col 38}{space 1}    76161{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_tables
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26311 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,988
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  76160{txt}){col 67}= {res}  52218.62
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9147
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8643
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7267
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,161{txt}{col 51}Root MSE{col 67}= {res}    6.4917

{txt}{ralign 84:(Std. err. adjusted for {res:76,161} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.32833{col 32}{space 2} .0738505{col 43}{space 1} -275.26{col 52}{space 3}0.000{col 60}{space 4}-20.47308{col 73}{space 3}-20.18359
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2106738{col 32}{space 2} .0751797{col 43}{space 1}    2.80{col 52}{space 3}0.005{col 60}{space 4}  .063322{col 73}{space 3} .3580256
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.005836{col 32}{space 2} .5346946{col 43}{space 1}    1.88{col 52}{space 3}0.060{col 60}{space 4}-.0421625{col 73}{space 3} 2.053835
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.532234{col 32}{space 2} .9926123{col 43}{space 1}   -3.56{col 52}{space 3}0.000{col 60}{space 4}-5.477749{col 73}{space 3}-1.586719
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.04038{col 32}{space 2} .0365116{col 43}{space 1} -384.55{col 52}{space 3}0.000{col 60}{space 4}-14.11194{col 73}{space 3}-13.96882
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.23024{col 32}{space 2}  .023589{col 43}{space 1} 1747.86{col 52}{space 3}0.000{col 60}{space 4} 41.18401{col 73}{space 3} 41.27648
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76161{col 38}{space 1}    76161{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_tables
{txt}
{com}. 
. * Make table
. esttab twoperiods_tables prepost_tables threeperiods_tables using 03_tables/tabled4.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled4.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled5.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & menorca_not_ciutadella == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32155 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,266
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59132{txt}){col 67}= {res}  10633.15
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8748
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4056
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,133{txt}{col 51}Root MSE{col 67}= {res}    5.2258

{txt}{ralign 84:(Std. err. adjusted for {res:59,133} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.130789{col 32}{space 2} .0630196{col 43}{space 1}  -97.28{col 52}{space 3}0.000{col 60}{space 4}-6.254307{col 73}{space 3} -6.00727
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0384034{col 32}{space 2} .0714038{col 43}{space 1}    0.54{col 52}{space 3}0.591{col 60}{space 4}-.1015485{col 73}{space 3} .1783552
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.176875{col 32}{space 2} .6933728{col 43}{space 1}    1.70{col 52}{space 3}0.090{col 60}{space 4}-.1821382{col 73}{space 3} 2.535889
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.143904{col 32}{space 2} 1.121948{col 43}{space 1}   -2.80{col 52}{space 3}0.005{col 60}{space 4}-5.342926{col 73}{space 3} -.944882
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.42166{col 32}{space 2} .0151956{col 43}{space 1} 1804.58{col 52}{space 3}0.000{col 60}{space 4} 27.39187{col 73}{space 3} 27.45144
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59133{col 38}{space 1}    59133{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_menorca_notciuta
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella if menorca_not_ciutadella == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26289 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,697
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  76052{txt}){col 67}= {res}  45120.33
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8201
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7138
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4239
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,053{txt}{col 51}Root MSE{col 67}= {res}    9.4298

{txt}{ralign 84:(Std. err. adjusted for {res:76,053} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.95539{col 32}{space 2} .0688113{col 43}{space 1} -188.27{col 52}{space 3}0.000{col 60}{space 4}-13.09026{col 73}{space 3}-12.82052
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.010137{col 32}{space 2}  .078023{col 43}{space 1}  -12.95{col 52}{space 3}0.000{col 60}{space 4}-1.163062{col 73}{space 3}-.8572125
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4396813{col 32}{space 2} .5894541{col 43}{space 1}    0.75{col 52}{space 3}0.456{col 60}{space 4}-.7156459{col 73}{space 3} 1.595008
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.471188{col 32}{space 2} 1.008378{col 43}{space 1}   -2.45{col 52}{space 3}0.014{col 60}{space 4}-4.447604{col 73}{space 3}-.4947723
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.61236{col 32}{space 2}  .011515{col 43}{space 1} 3005.84{col 52}{space 3}0.000{col 60}{space 4} 34.58979{col 73}{space 3} 34.63493
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76053{col 38}{space 1}    76053{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_menorca_notciuta
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period if menorca_not_ciutadella == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26289 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,697
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  76052{txt}){col 67}= {res}  52274.59
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9148
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8645
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7272
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,053{txt}{col 51}Root MSE{col 67}= {res}    6.4885

{txt}{ralign 84:(Std. err. adjusted for {res:76,053} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.35582{col 32}{space 2} .0739228{col 43}{space 1} -275.37{col 52}{space 3}0.000{col 60}{space 4}-20.50071{col 73}{space 3}-20.21094
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2266209{col 32}{space 2} .0752643{col 43}{space 1}    3.01{col 52}{space 3}0.003{col 60}{space 4} .0791032{col 73}{space 3} .3741385
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .8163838{col 32}{space 2} .5892535{col 43}{space 1}    1.39{col 52}{space 3}0.166{col 60}{space 4}-.3385503{col 73}{space 3} 1.971318
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.707946{col 32}{space 2} 1.008175{col 43}{space 1}   -3.68{col 52}{space 3}0.000{col 60}{space 4}-5.683965{col 73}{space 3}-1.731928
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.04747{col 32}{space 2} .0365178{col 43}{space 1} -384.67{col 52}{space 3}0.000{col 60}{space 4}-14.11904{col 73}{space 3}-13.97589
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.22459{col 32}{space 2} .0235857{col 43}{space 1} 1747.86{col 52}{space 3}0.000{col 60}{space 4} 41.17836{col 73}{space 3} 41.27081
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76053{col 38}{space 1}    76053{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeper_menorca_notciuta
{txt}
{com}. 
. * Make table
. esttab twoperiods_menorca_notciuta prepost_menorca_notciuta threeper_menorca_notciuta using 03_tables/tabled5.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled5.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled6.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/balearic_plus_ciutadella.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 116 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     4,988
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}   2493{txt}){col 67}= {res}    523.48
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8471
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6938
{txt}{col 51}Within R-sq.{col 67}= {res}    0.2334
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}     2,494{txt}{col 51}Root MSE{col 67}= {res}    6.1161

{txt}{ralign 84:(Std. err. adjusted for {res:2,494} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} 3.311371{col 32}{space 2} .2367953{col 43}{space 1}   13.98{col 52}{space 3}0.000{col 60}{space 4} 2.847036{col 73}{space 3} 3.775707
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 3.863518{col 32}{space 2} .2980471{col 43}{space 1}   12.96{col 52}{space 3}0.000{col 60}{space 4} 3.279072{col 73}{space 3} 4.447963
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} -9.44922{col 32}{space 2} .4591344{col 43}{space 1}  -20.58{col 52}{space 3}0.000{col 60}{space 4}-10.34954{col 73}{space 3}-8.548896
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-5.785083{col 32}{space 2} 1.010611{col 43}{space 1}   -5.72{col 52}{space 3}0.000{col 60}{space 4}-7.766805{col 73}{space 3} -3.80336
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 26.87835{col 32}{space 2} .0865808{col 43}{space 1}  310.44{col 52}{space 3}0.000{col 60}{space 4} 26.70857{col 73}{space 3} 27.04812
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}     2494{col 38}{space 1}     2494{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_ddd_balearic
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 186 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     7,331
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}   2518{txt}){col 67}= {res}    605.21
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4601
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1770
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0656
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}     2,519{txt}{col 51}Root MSE{col 67}= {res}   11.6662

{txt}{ralign 84:(Std. err. adjusted for {res:2,519} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-5.060086{col 32}{space 2} .2447877{col 43}{space 1}  -20.67{col 52}{space 3}0.000{col 60}{space 4}-5.540091{col 73}{space 3} -4.58008
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 4.483275{col 32}{space 2} .3021298{col 43}{space 1}   14.84{col 52}{space 3}0.000{col 60}{space 4} 3.890827{col 73}{space 3} 5.075723
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-9.347174{col 32}{space 2} .4354706{col 43}{space 1}  -21.46{col 52}{space 3}0.000{col 60}{space 4}-10.20109{col 73}{space 3}-8.493257
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-6.073047{col 32}{space 2} .9431975{col 43}{space 1}   -6.44{col 52}{space 3}0.000{col 60}{space 4}-7.922569{col 73}{space 3}-4.223525
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  35.2196{col 32}{space 2} .0610412{col 43}{space 1}  576.98{col 52}{space 3}0.000{col 60}{space 4} 35.09991{col 73}{space 3}  35.3393
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}     2519{col 38}{space 1}     2519{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_ddd_balearic
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 186 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     7,331
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}   2518{txt}){col 67}= {res}   1360.66
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.7555
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6272
{txt}{col 51}Within R-sq.{col 67}= {res}    0.5768
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}     2,519{txt}{col 51}Root MSE{col 67}= {res}    7.8518

{txt}{ralign 84:(Std. err. adjusted for {res:2,519} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-14.28716{col 32}{space 2} .3173385{col 43}{space 1}  -45.02{col 52}{space 3}0.000{col 60}{space 4}-14.90943{col 73}{space 3}-13.66489
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 4.432166{col 32}{space 2} .2929286{col 43}{space 1}   15.13{col 52}{space 3}0.000{col 60}{space 4} 3.857761{col 73}{space 3} 5.006572
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-8.838635{col 32}{space 2} .4364059{col 43}{space 1}  -20.25{col 52}{space 3}0.000{col 60}{space 4}-9.694386{col 73}{space 3}-7.982884
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-6.021938{col 32}{space 2} .9403472{col 43}{space 1}   -6.40{col 52}{space 3}0.000{col 60}{space 4}-7.865871{col 73}{space 3}-4.178005
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-17.43707{col 32}{space 2} .2511476{col 43}{space 1}  -69.43{col 52}{space 3}0.000{col 60}{space 4}-17.92955{col 73}{space 3} -16.9446
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 44.33115{col 32}{space 2} .1632511{col 43}{space 1}  271.55{col 52}{space 3}0.000{col 60}{space 4} 44.01103{col 73}{space 3} 44.65127
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}     2519{col 38}{space 1}     2519{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_ddd_balearic
{txt}
{com}. 
. * Make table
. esttab twoperiods_ddd_balearic prepost_ddd_balearic threeperiods_ddd_balearic using 03_tables/tabled6.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled6.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled7.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/balearic_plus_ciutadella.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & menorca == 1 , absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 6 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       504
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}    251{txt}){col 67}= {res}    111.49
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9333
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8647
{txt}{col 51}Within R-sq.{col 67}= {res}    0.5873
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}       252{txt}{col 51}Root MSE{col 67}= {res}    3.2610

{txt}{ralign 84:(Std. err. adjusted for {res:252} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-3.131429{col 32}{space 2} .5229786{col 43}{space 1}   -5.99{col 52}{space 3}0.000{col 60}{space 4}-4.161414{col 73}{space 3}-2.101443
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}     9.66{col 32}{space 2} .8749137{col 43}{space 1}   11.04{col 52}{space 3}0.000{col 60}{space 4} 7.936892{col 73}{space 3} 11.38311
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} -3.00642{col 32}{space 2} .6556771{col 43}{space 1}   -4.59{col 52}{space 3}0.000{col 60}{space 4} -4.29775{col 73}{space 3} -1.71509
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-11.58156{col 32}{space 2} 1.306928{col 43}{space 1}   -8.86{col 52}{space 3}0.000{col 60}{space 4}-14.15551{col 73}{space 3}-9.007622
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  32.1203{col 32}{space 2}  .144964{col 43}{space 1}  221.57{col 52}{space 3}0.000{col 60}{space 4}  31.8348{col 73}{space 3}  32.4058
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}      252{col 38}{space 1}      252{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_ddd_menorca
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella if menorca == 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 16 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       730
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}    252{txt}){col 67}= {res}    523.28
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.6298
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4294
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3959
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}       253{txt}{col 51}Root MSE{col 67}= {res}    7.8509

{txt}{ralign 84:(Std. err. adjusted for {res:253} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.358728{col 32}{space 2} .5646694{col 43}{space 1}  -11.26{col 52}{space 3}0.000{col 60}{space 4}-7.470801{col 73}{space 3}-5.246656
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 6.730818{col 32}{space 2} 1.033938{col 43}{space 1}    6.51{col 52}{space 3}0.000{col 60}{space 4} 4.694556{col 73}{space 3} 8.767079
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-8.048532{col 32}{space 2} .6705781{col 43}{space 1}  -12.00{col 52}{space 3}0.000{col 60}{space 4}-9.369183{col 73}{space 3} -6.72788
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -8.32059{col 32}{space 2} 1.369014{col 43}{space 1}   -6.08{col 52}{space 3}0.000{col 60}{space 4}-11.01676{col 73}{space 3}-5.624424
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 38.06409{col 32}{space 2} .1055714{col 43}{space 1}  360.55{col 52}{space 3}0.000{col 60}{space 4} 37.85618{col 73}{space 3} 38.27201
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}      253{col 38}{space 1}      253{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_ddd_menorca
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period if menorca == 1 , absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 16 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       730
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}    252{txt}){col 67}= {res}    512.27
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8690
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7977
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7863
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}       253{txt}{col 51}Root MSE{col 67}= {res}    4.6741

{txt}{ralign 84:(Std. err. adjusted for {res:253} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-13.66513{col 32}{space 2} .7634309{col 43}{space 1}  -17.90{col 52}{space 3}0.000{col 60}{space 4}-15.16865{col 73}{space 3}-12.16161
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 6.494382{col 32}{space 2}  .997023{col 43}{space 1}    6.51{col 52}{space 3}0.000{col 60}{space 4} 4.530823{col 73}{space 3} 8.457942
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} -7.13922{col 32}{space 2} .7131768{col 43}{space 1}  -10.01{col 52}{space 3}0.000{col 60}{space 4}-8.543766{col 73}{space 3}-5.734674
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-8.084154{col 32}{space 2} 1.341706{col 43}{space 1}   -6.03{col 52}{space 3}0.000{col 60}{space 4}-10.72654{col 73}{space 3}-5.441768
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-12.79418{col 32}{space 2} .5084243{col 43}{space 1}  -25.16{col 52}{space 3}0.000{col 60}{space 4}-13.79548{col 73}{space 3}-11.79288
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 44.88508{col 32}{space 2} .3262764{col 43}{space 1}  137.57{col 52}{space 3}0.000{col 60}{space 4}  44.2425{col 73}{space 3} 45.52766
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}      253{col 38}{space 1}      253{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_ddd_menorca
{txt}
{com}. 
. * Make table
. esttab twoperiods_ddd_menorca prepost_ddd_menorca threeperiods_ddd_menorca using 03_tables/tabled7.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled7.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled8.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/balearic_plus_ciutadella.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & (ciutadella == 1 | mallorca == 1), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 95 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     4,098
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}   2048{txt}){col 67}= {res}    448.15
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8200
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6393
{txt}{col 51}Within R-sq.{col 67}= {res}    0.2548
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}     2,049{txt}{col 51}Root MSE{col 67}= {res}    6.2328

{txt}{ralign 84:(Std. err. adjusted for {res:2,049} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} 3.973507{col 32}{space 2} .2698277{col 43}{space 1}   14.73{col 52}{space 3}0.000{col 60}{space 4} 3.444342{col 73}{space 3} 4.502673
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 3.228877{col 32}{space 2} .3381498{col 43}{space 1}    9.55{col 52}{space 3}0.000{col 60}{space 4} 2.565724{col 73}{space 3} 3.892031
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-10.11136{col 32}{space 2} .4770533{col 43}{space 1}  -21.20{col 52}{space 3}0.000{col 60}{space 4}-11.04692{col 73}{space 3}-9.175796
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-5.150442{col 32}{space 2} 1.023275{col 43}{space 1}   -5.03{col 52}{space 3}0.000{col 60}{space 4}-7.157209{col 73}{space 3}-3.143674
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 25.20978{col 32}{space 2} .0973405{col 43}{space 1}  258.99{col 52}{space 3}0.000{col 60}{space 4} 25.01889{col 73}{space 3} 25.40068
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}     2049{col 38}{space 1}     2049{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_ddd_mallorca
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella if (ciutadella == 1 | mallorca == 1), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 153 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     6,053
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}   2071{txt}){col 67}= {res}    579.06
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.3803
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0570
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0644
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}     2,072{txt}{col 51}Root MSE{col 67}= {res}   12.2646

{txt}{ralign 84:(Std. err. adjusted for {res:2,072} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-5.130331{col 32}{space 2} .2879499{col 43}{space 1}  -17.82{col 52}{space 3}0.000{col 60}{space 4}-5.695032{col 73}{space 3}-4.565629
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 4.367989{col 32}{space 2} .3444613{col 43}{space 1}   12.68{col 52}{space 3}0.000{col 60}{space 4} 3.692463{col 73}{space 3} 5.043516
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-9.276929{col 32}{space 2} .4611452{col 43}{space 1}  -20.12{col 52}{space 3}0.000{col 60}{space 4}-10.18129{col 73}{space 3}-8.372573
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-5.957761{col 32}{space 2} .9576812{col 43}{space 1}   -6.22{col 52}{space 3}0.000{col 60}{space 4}-7.835879{col 73}{space 3}-4.079643
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.12445{col 32}{space 2} .0702193{col 43}{space 1}  485.97{col 52}{space 3}0.000{col 60}{space 4} 33.98674{col 73}{space 3} 34.26215
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}     2072{col 38}{space 1}     2072{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_ddd_mallorca
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period  if (ciutadella == 1 | mallorca == 1), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 153 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     6,053
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}   2071{txt}){col 67}= {res}   1237.96
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.7243
{txt}{col 51}Adj R-squared{col 67}= {res}    0.5803
{txt}{col 51}Within R-sq.{col 67}= {res}    0.5836
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}     2,072{txt}{col 51}Root MSE{col 67}= {res}    8.1825

{txt}{ralign 84:(Std. err. adjusted for {res:2,072} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-14.82275{col 32}{space 2} .3727411{col 43}{space 1}  -39.77{col 52}{space 3}0.000{col 60}{space 4}-15.55373{col 73}{space 3}-14.09176
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 4.442523{col 32}{space 2} .3373113{col 43}{space 1}   13.17{col 52}{space 3}0.000{col 60}{space 4} 3.781018{col 73}{space 3} 5.104027
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-8.797905{col 32}{space 2} .4617805{col 43}{space 1}  -19.05{col 52}{space 3}0.000{col 60}{space 4}-9.703508{col 73}{space 3}-7.892303
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-6.032295{col 32}{space 2}  .955204{col 43}{space 1}   -6.32{col 52}{space 3}0.000{col 60}{space 4}-7.905555{col 73}{space 3}-4.159034
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-18.42678{col 32}{space 2} .2859877{col 43}{space 1}  -64.43{col 52}{space 3}0.000{col 60}{space 4}-18.98764{col 73}{space 3}-17.86593
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 43.67906{col 32}{space 2} .1871117{col 43}{space 1}  233.44{col 52}{space 3}0.000{col 60}{space 4} 43.31212{col 73}{space 3} 44.04601
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}     2072{col 38}{space 1}     2072{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_ddd_mallorca
{txt}
{com}. 
. * Make table
. esttab twoperiods_ddd_mallorca prepost_ddd_mallorca threeperiods_ddd_mallorca using 03_tables/tabled8.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled8.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled9.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##menorca if period > 1 & ciutadella == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 32160 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.menorca{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.menorca{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.menorca omitted because of collinearity
{txt}note: 1.ep#1.menorca omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,362
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59180{txt}){col 67}= {res}  10629.21
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9375
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8750
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4055
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,181{txt}{col 51}Root MSE{col 67}= {res}    5.2250

{txt}{ralign 81:(Std. err. adjusted for {res:59,181} clusters in {res:mesa_code_elecspecific})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   pp_voteshare{col 17}{c |} Coefficient{col 29}  std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.post {c |}{col 17}{res}{space 2}-6.130789{col 29}{space 2} .0630196{col 40}{space 1}  -97.28{col 49}{space 3}0.000{col 57}{space 4}-6.254307{col 70}{space 3} -6.00727
{txt}{space 11}1.ep {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 8}post#ep {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .0384034{col 29}{space 2} .0714038{col 40}{space 1}    0.54{col 49}{space 3}0.591{col 57}{space 4}-.1015484{col 70}{space 3} .1783552
{txt}{space 15} {c |}
{space 6}1.menorca {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 3}post#menorca {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} 2.423542{col 29}{space 2} .6617132{col 40}{space 1}    3.66{col 49}{space 3}0.000{col 57}{space 4} 1.126582{col 70}{space 3} 3.720503
{txt}{space 15} {c |}
{space 5}ep#menorca {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
post#ep#menorca {c |}
{space 9}1 1 1  {c |}{col 17}{res}{space 2} 10.19741{col 29}{space 2} .9618391{col 40}{space 1}   10.60{col 49}{space 3}0.000{col 57}{space 4} 8.312206{col 70}{space 3} 12.08262
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 27.43683{col 29}{space 2} .0151872{col 40}{space 1} 1806.57{col 49}{space 3}0.000{col 57}{space 4} 27.40707{col 70}{space 3}  27.4666
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59181{col 38}{space 1}    59181{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods_ddd_menplcb
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##menorca if ciutadella == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.menorca{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.menorca{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.menorca omitted because of collinearity
{txt}note: 1.ep#1.menorca omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,818
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  76101{txt}){col 67}= {res}  44923.70
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8202
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7139
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4237
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,102{txt}{col 51}Root MSE{col 67}= {res}    9.4274

{txt}{ralign 81:(Std. err. adjusted for {res:76,102} clusters in {res:mesa_code_elecspecific})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   pp_voteshare{col 17}{c |} Coefficient{col 29}  std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.post {c |}{col 17}{res}{space 2}-12.95539{col 29}{space 2} .0688113{col 40}{space 1} -188.27{col 49}{space 3}0.000{col 57}{space 4}-13.09026{col 70}{space 3}-12.82052
{txt}{space 11}1.ep {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 8}post#ep {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}-1.010137{col 29}{space 2}  .078023{col 40}{space 1}  -12.95{col 49}{space 3}0.000{col 57}{space 4}-1.163062{col 70}{space 3}-.8572125
{txt}{space 15} {c |}
{space 6}1.menorca {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 3}post#menorca {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} 7.801888{col 29}{space 2} .7084319{col 40}{space 1}   11.01{col 49}{space 3}0.000{col 57}{space 4} 6.413365{col 70}{space 3} 9.190411
{txt}{space 15} {c |}
{space 5}ep#menorca {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
post#ep#menorca {c |}
{space 9}1 1 1  {c |}{col 17}{res}{space 2} 6.535727{col 29}{space 2} 1.116407{col 40}{space 1}    5.85{col 49}{space 3}0.000{col 57}{space 4} 4.347574{col 70}{space 3} 8.723879
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 34.61868{col 29}{space 2} .0115109{col 40}{space 1} 3007.48{col 49}{space 3}0.000{col 57}{space 4} 34.59612{col 70}{space 3} 34.64124
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76102{col 38}{space 1}    76102{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_ddd_menplcb
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##menorca i.period  if ciutadella == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26303 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.menorca{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.menorca{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.menorca omitted because of collinearity
{txt}note: 1.ep#1.menorca omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,818
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  76101{txt}){col 67}= {res}  52069.70
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9148
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8644
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7268
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,102{txt}{col 51}Root MSE{col 67}= {res}    6.4907

{txt}{ralign 81:(Std. err. adjusted for {res:76,102} clusters in {res:mesa_code_elecspecific})}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   pp_voteshare{col 17}{c |} Coefficient{col 29}  std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.post {c |}{col 17}{res}{space 2}-20.35036{col 29}{space 2}  .073924{col 40}{space 1} -275.29{col 49}{space 3}0.000{col 57}{space 4}-20.49525{col 70}{space 3}-20.20547
{txt}{space 11}1.ep {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 8}post#ep {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2} .2257077{col 29}{space 2} .0752646{col 40}{space 1}    3.00{col 49}{space 3}0.003{col 57}{space 4} .0781895{col 70}{space 3}  .373226
{txt}{space 15} {c |}
{space 6}1.menorca {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 3}post#menorca {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}  6.88258{col 29}{space 2} .7932997{col 40}{space 1}    8.68{col 49}{space 3}0.000{col 57}{space 4} 5.327717{col 70}{space 3} 8.437444
{txt}{space 15} {c |}
{space 5}ep#menorca {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
post#ep#menorca {c |}
{space 9}1 1 1  {c |}{col 17}{res}{space 2}  5.33856{col 29}{space 2}  1.12692{col 40}{space 1}    4.74{col 49}{space 3}0.000{col 57}{space 4} 3.129803{col 70}{space 3} 7.547318
{txt}{space 15} {c |}
{space 9}period {c |}
{space 13}2  {c |}{col 17}{res}{space 2} -14.0371{col 29}{space 2}  .036539{col 40}{space 1} -384.17{col 49}{space 3}0.000{col 57}{space 4}-14.10871{col 70}{space 3}-13.96548
{txt}{space 13}3  {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 41.22774{col 29}{space 2} .0235967{col 40}{space 1} 1747.18{col 49}{space 3}0.000{col 57}{space 4} 41.18149{col 70}{space 3} 41.27399
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76102{col 38}{space 1}    76102{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_ddd_menplcb
{txt}
{com}. 
. * Make table
. esttab twoperiods_ddd_menplcb prepost_ddd_menplcb threeperiods_ddd_menplcb using 03_tables/tabled9.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.menorca 1.post#1.ep#1.menorca 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1.menorca "Menorca (outside of Ciutadella) in 2019" 1.post#1.ep#1.menorca "EP 2019 x Menorca" 2.period "2014-2015 election" post#ep#menorca "EP 2019 x Menorca" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type") 
{res}{txt}(output written to {browse  `"03_tables/tabled9.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled10.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/elections_ciutadella.dta, clear
{txt}
{com}. 
. * No fixed effects
. regr pp_voteshare ep if year == 2019, cluster(table_code_notelectionspecific)

{txt}Linear regression                               Number of obs     = {res}       112
                                                {txt}F(1, 27)          =  {res}    74.19
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0636
                                                {txt}Root MSE          =    {res} 2.8336

{txt}{ralign 78:(Std. err. adjusted for {res:28} clusters in {res:table_code_notelectionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}ep {c |}{col 14}{res}{space 2}-1.690054{col 26}{space 2} .1962152{col 37}{space 1}   -8.61{col 46}{space 3}0.000{col 54}{space 4}-2.092655{col 67}{space 3}-1.287454
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 21.91003{col 26}{space 2} .5264531{col 37}{space 1}   41.62{col 46}{space 3}0.000{col 54}{space 4} 20.82984{col 67}{space 3} 22.99022
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store cross_section1
{txt}
{com}. estadd local  FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. * With voting station fixed effects
. regr pp_voteshare ep i.table_code_notelectionspecific if year == 2019, cluster(table_code_notelectionspecific)

{txt}Linear regression                               Number of obs     = {res}       112
                                                {txt}{help j_robustsingular:F(0, 27) }         =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.9213
                                                {txt}Root MSE          =    {res}  .9458

{txt}{ralign 96:(Std. err. adjusted for {res:28} clusters in {res:table_code_notelectionspecific})}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  pp_voteshare{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 28}ep {c |}{col 32}{res}{space 2}-1.690054{col 44}{space 2} .2258863{col 55}{space 1}   -7.48{col 64}{space 3}0.000{col 72}{space 4}-2.153535{col 85}{space 3}-1.226574
{txt}{space 30} {c |}
table_code_notelectionspecific {c |}
{space 19}0701501002  {c |}{col 32}{res}{space 2}-4.197183{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501003A  {c |}{col 32}{res}{space 2}-5.494924{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501003B  {c |}{col 32}{res}{space 2}-1.105717{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501004A  {c |}{col 32}{res}{space 2}-7.641188{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501004B  {c |}{col 32}{res}{space 2}-7.826384{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501005A  {c |}{col 32}{res}{space 2}-.2454538{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501005B  {c |}{col 32}{res}{space 2}  -.89465{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502001U  {c |}{col 32}{res}{space 2} .0257592{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502002A  {c |}{col 32}{res}{space 2}-4.208354{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502002B  {c |}{col 32}{res}{space 2}-2.544674{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502003A  {c |}{col 32}{res}{space 2}-4.038512{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502003B  {c |}{col 32}{res}{space 2}-2.515619{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 19}0701502004  {c |}{col 32}{res}{space 2}-2.004235{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503001A  {c |}{col 32}{res}{space 2}-1.152445{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503001B  {c |}{col 32}{res}{space 2} 3.056869{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503002A  {c |}{col 32}{res}{space 2}-2.554738{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503002B  {c |}{col 32}{res}{space 2}  -.35847{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503003A  {c |}{col 32}{res}{space 2}-3.088308{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503003B  {c |}{col 32}{res}{space 2}-.3049059{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504001A  {c |}{col 32}{res}{space 2} 1.120821{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504001B  {c |}{col 32}{res}{space 2} 3.603041{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504002A  {c |}{col 32}{res}{space 2}-2.944407{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504002B  {c |}{col 32}{res}{space 2} .3941302{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504003A  {c |}{col 32}{res}{space 2}-4.593906{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504003B  {c |}{col 32}{res}{space 2}-.4619741{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504004A  {c |}{col 32}{res}{space 2} .4198308{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504004B  {c |}{col 32}{res}{space 2}-2.997019{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 30} {c |}
{space 25}_cons {c |}{col 32}{res}{space 2} 23.78691{col 44}{space 2} .0564716{col 55}{space 1}  421.22{col 64}{space 3}0.000{col 72}{space 4} 23.67104{col 85}{space 3} 23.90278
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store cross_section2
{txt}
{com}. estadd local  FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. * With dummies for each election type
. regr pp_voteshare ep municipal autonomic if year == 2019, cluster(table_code_notelectionspecific)

{txt}Linear regression                               Number of obs     = {res}       112
                                                {txt}F(3, 27)          =  {res}    34.75
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0665
                                                {txt}Root MSE          =    {res} 2.8552

{txt}{ralign 78:(Std. err. adjusted for {res:28} clusters in {res:table_code_notelectionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}ep {c |}{col 14}{res}{space 2}-1.717379{col 26}{space 2} .2025925{col 37}{space 1}   -8.48{col 46}{space 3}0.000{col 54}{space 4}-2.133064{col 67}{space 3}-1.301693
{txt}{space 3}municipal {c |}{col 14}{res}{space 2} .1805841{col 26}{space 2} .2956032{col 37}{space 1}    0.61{col 46}{space 3}0.546{col 54}{space 4}-.4259436{col 67}{space 3} .7871118
{txt}{space 3}autonomic {c |}{col 14}{res}{space 2}-.2625574{col 26}{space 2} .2317561{col 37}{space 1}   -1.13{col 46}{space 3}0.267{col 54}{space 4}-.7380816{col 67}{space 3} .2129668
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 21.93736{col 26}{space 2} .5305449{col 37}{space 1}   41.35{col 46}{space 3}0.000{col 54}{space 4} 20.84877{col 67}{space 3} 23.02594
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store cross_section3
{txt}
{com}. estadd local  FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. * With dummies for each election type and voting station fixed effects
. regr pp_voteshare ep municipal autonomic i.table_code_notelectionspecific if year == 2019, cluster(table_code_notelectionspecific)

{txt}Linear regression                               Number of obs     = {res}       112
                                                {txt}{help j_robustsingular:F(2, 27) }         =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.9242
                                                {txt}Root MSE          =    {res} .93931

{txt}{ralign 96:(Std. err. adjusted for {res:28} clusters in {res:table_code_notelectionspecific})}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  pp_voteshare{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 28}ep {c |}{col 32}{res}{space 2}-1.717379{col 44}{space 2} .2339336{col 55}{space 1}   -7.34{col 64}{space 3}0.000{col 72}{space 4}-2.197371{col 85}{space 3}-1.237387
{txt}{space 21}municipal {c |}{col 32}{res}{space 2} .1805841{col 44}{space 2} .3413332{col 55}{space 1}    0.53{col 64}{space 3}0.601{col 72}{space 4}-.5197738{col 85}{space 3}  .880942
{txt}{space 21}autonomic {c |}{col 32}{res}{space 2}-.2625574{col 44}{space 2} .2676089{col 55}{space 1}   -0.98{col 64}{space 3}0.335{col 72}{space 4}-.8116455{col 85}{space 3} .2865307
{txt}{space 30} {c |}
table_code_notelectionspecific {c |}
{space 19}0701501002  {c |}{col 32}{res}{space 2}-4.197183{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501003A  {c |}{col 32}{res}{space 2}-5.494924{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501003B  {c |}{col 32}{res}{space 2}-1.105717{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501004A  {c |}{col 32}{res}{space 2}-7.641188{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501004B  {c |}{col 32}{res}{space 2}-7.826384{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501005A  {c |}{col 32}{res}{space 2}-.2454538{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701501005B  {c |}{col 32}{res}{space 2}  -.89465{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502001U  {c |}{col 32}{res}{space 2} .0257592{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502002A  {c |}{col 32}{res}{space 2}-4.208354{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502002B  {c |}{col 32}{res}{space 2}-2.544674{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502003A  {c |}{col 32}{res}{space 2}-4.038512{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701502003B  {c |}{col 32}{res}{space 2}-2.515619{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 19}0701502004  {c |}{col 32}{res}{space 2}-2.004235{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503001A  {c |}{col 32}{res}{space 2}-1.152445{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503001B  {c |}{col 32}{res}{space 2} 3.056869{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503002A  {c |}{col 32}{res}{space 2}-2.554738{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503002B  {c |}{col 32}{res}{space 2}  -.35847{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503003A  {c |}{col 32}{res}{space 2}-3.088308{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701503003B  {c |}{col 32}{res}{space 2}-.3049059{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504001A  {c |}{col 32}{res}{space 2} 1.120821{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504001B  {c |}{col 32}{res}{space 2} 3.603041{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504002A  {c |}{col 32}{res}{space 2}-2.944407{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504002B  {c |}{col 32}{res}{space 2} .3941302{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504003A  {c |}{col 32}{res}{space 2}-4.593906{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504003B  {c |}{col 32}{res}{space 2}-.4619741{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504004A  {c |}{col 32}{res}{space 2} .4198308{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 18}0701504004B  {c |}{col 32}{res}{space 2}-2.997019{col 44}{space 2}        .{col 55}{space 1}       .{col 64}{space 3}    .{col 72}{space 4}        .{col 85}{space 3}        .
{txt}{space 30} {c |}
{space 25}_cons {c |}{col 32}{res}{space 2} 23.81423{col 44}{space 2} .1683037{col 55}{space 1}  141.50{col 64}{space 3}0.000{col 72}{space 4}  23.4689{col 85}{space 3} 24.15957
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store cross_section4
{txt}
{com}. estadd local  FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. * Make table
. esttab cross_section1 cross_section2 cross_section3 cross_section4 using 03_tables/tabled10.tex, tex se replace nomtitles keep(ep municipal autonomic _cons) coeflabels (ep "European election" municipal "Municipal election" autonomic "Autonomic election" _cons "Constant") s(FE, label("Voting station fixed effects")) star(* 0.10 ** 0.05 *** 0.01) addnotes("Standard errors are clustered by voting station" "In models 3 and 4, the reference category are Elections for the Balearic Council.") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/tabled10.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled11.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/elections_ciutadella.dta, clear
{txt}
{com}. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep  if period > 1 , absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       224
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res}    111{txt}){col 67}= {res}    160.77
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8424
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6806
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7457
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    2.7794

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-6.137849{col 26}{space 2} .3966734{col 37}{space 1}  -15.47{col 46}{space 3}0.000{col 54}{space 4}-6.923884{col 67}{space 3}-5.351814
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-1.921565{col 26}{space 2} .9737946{col 37}{space 1}   -1.97{col 46}{space 3}0.051{col 54}{space 4}-3.851204{col 67}{space 3} .0080743
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 28.10576{col 26}{space 2} .1857028{col 37}{space 1}  151.35{col 46}{space 3}0.000{col 54}{space 4} 27.73778{col 67}{space 3} 28.47374
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store twoperiods
{txt}
{com}. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep, absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       336
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res}    111{txt}){col 67}= {res}    977.67
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.5439
{txt}{col 51}Adj R-squared{col 67}= {res}    0.3117
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4957
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    8.6697

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-14.40726{col 26}{space 2} .3626902{col 37}{space 1}  -39.72{col 46}{space 3}0.000{col 54}{space 4}-15.12595{col 67}{space 3}-13.68857
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-1.589772{col 26}{space 2} .8997809{col 37}{space 1}   -1.77{col 46}{space 3}0.080{col 54}{space 4}-3.372748{col 67}{space 3} .1932039
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 36.29222{col 26}{space 2} .1137114{col 37}{space 1}  319.16{col 46}{space 3}0.000{col 54}{space 4} 36.06689{col 67}{space 3} 36.51755
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep i.period, absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       336
{txt}Absorbing 1 HDFE group{col 51}F({res}   3{txt},{res}    111{txt}){col 67}= {res}   1337.71
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9542
{txt}{col 51}Adj R-squared{col 67}= {res}    0.9306
{txt}{col 51}Within R-sq.{col 67}= {res}    0.9494
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    2.7524

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-22.59372{col 26}{space 2} .4078674{col 37}{space 1}  -55.39{col 46}{space 3}0.000{col 54}{space 4}-23.40194{col 67}{space 3}-21.78551
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-1.589772{col 26}{space 2}  .901135{col 37}{space 1}   -1.76{col 46}{space 3}0.080{col 54}{space 4}-3.375431{col 67}{space 3} .1958871
{txt}{space 12} {c |}
{space 6}period {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-16.37293{col 26}{space 2} .3408076{col 37}{space 1}  -48.04{col 46}{space 3}0.000{col 54}{space 4}-17.04826{col 67}{space 3}-15.69759
{txt}{space 10}3  {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 44.47868{col 26}{space 2} .2110707{col 37}{space 1}  210.73{col 46}{space 3}0.000{col 54}{space 4} 44.06043{col 67}{space 3} 44.89693
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods
{txt}
{com}. 
. * 2009/11-2014/5 (Placebo)
. reghdfe pp_voteshare_lag post##ep, absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       224
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res}    111{txt}){col 67}= {res}   1236.59
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9631
{txt}{col 51}Adj R-squared{col 67}= {res}    0.9252
{txt}{col 51}Within R-sq.{col 67}= {res}    0.9548
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    0.0254

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_votesha~g{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-.1653882{col 26}{space 2} .0036099{col 37}{space 1}  -45.82{col 46}{space 3}0.000{col 54}{space 4}-.1725415{col 67}{space 3} -.158235
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0066359{col 26}{space 2} .0089661{col 37}{space 1}    0.74{col 46}{space 3}0.461{col 54}{space 4} -.011131{col 67}{space 3} .0244028
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} .4447868{col 26}{space 2} .0016985{col 37}{space 1}  261.87{col 46}{space 3}0.000{col 54}{space 4} .4414211{col 67}{space 3} .4481526
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store placebo
{txt}
{com}. 
. * Make table
. esttab twoperiods prepost threeperiods placebo using 03_tables/tabled11.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019" "Placebo with lagged outcome")  keep (1.post 1.post#1.ep 2.period) coeflabels (1.post#1.ep "Treatment (absence of booth)" 1.post "2019" 2.period "2014-5") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type")
{res}{txt}(output written to {browse  `"03_tables/tabled11.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled12.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/elections_ciutadella_more_years, clear
{txt}
{com}. 
. * Grouping 2003 and 2004 together
. * Pre vs. post
. reghdfe pp_voteshare post##ep if period3 != ., absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       420
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res}    111{txt}){col 67}= {res}   1412.96
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.5651
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4044
{txt}{col 51}Within R-sq.{col 67}= {res}    0.5151
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    8.6968

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-15.91934{col 26}{space 2} .3465982{col 37}{space 1}  -45.93{col 46}{space 3}0.000{col 54}{space 4}-16.60614{col 67}{space 3}-15.23253
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-5.028055{col 26}{space 2} .8559697{col 37}{space 1}   -5.87{col 46}{space 3}0.000{col 54}{space 4}-6.724216{col 67}{space 3}-3.331894
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 38.73679{col 26}{space 2} .0867622{col 37}{space 1}  446.47{col 46}{space 3}0.000{col 54}{space 4} 38.56487{col 67}{space 3} 38.90872
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_period3
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep i.period3 if period3 != ., absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 4.period3 omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       420
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}    111{txt}){col 67}= {res}   1152.81
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9395
{txt}{col 51}Adj R-squared{col 67}= {res}    0.9166
{txt}{col 51}Within R-sq.{col 67}= {res}    0.9326
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    3.2537

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-23.03427{col 26}{space 2} .5911805{col 37}{space 1}  -38.96{col 46}{space 3}0.000{col 54}{space 4}-24.20574{col 67}{space 3}-21.86281
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-4.079396{col 26}{space 2} .8706727{col 37}{space 1}   -4.69{col 46}{space 3}0.000{col 54}{space 4}-5.804693{col 67}{space 3}  -2.3541
{txt}{space 12} {c |}
{space 5}period3 {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-1.062957{col 26}{space 2}  .580322{col 37}{space 1}   -1.83{col 46}{space 3}0.070{col 54}{space 4}-2.212904{col 67}{space 3} .0869894
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-17.43588{col 26}{space 2}  .586264{col 37}{space 1}  -29.74{col 46}{space 3}0.000{col 54}{space 4} -18.5976{col 67}{space 3}-16.27416
{txt}{space 10}4  {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 45.50389{col 26}{space 2} .4246202{col 37}{space 1}  107.16{col 46}{space 3}0.000{col 54}{space 4} 44.66248{col 67}{space 3}  46.3453
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_period3
{txt}
{com}. 
. * Grouping 2004 and 2007 together
. * Pre vs. post
. reghdfe pp_voteshare post##ep if period2 != ., absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       448
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res}    111{txt}){col 67}= {res}   1195.37
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.5629
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4151
{txt}{col 51}Within R-sq.{col 67}= {res}    0.5157
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    8.8495

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-17.19974{col 26}{space 2}  .420358{col 37}{space 1}  -40.92{col 46}{space 3}0.000{col 54}{space 4}-18.03271{col 67}{space 3}-16.36678
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-3.747646{col 26}{space 2} .8882965{col 37}{space 1}   -4.22{col 46}{space 3}0.000{col 54}{space 4}-5.507865{col 67}{space 3}-1.987427
{txt}{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 39.62417{col 26}{space 2} .0927589{col 37}{space 1}  427.17{col 46}{space 3}0.000{col 54}{space 4} 39.44037{col 67}{space 3} 39.80798
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store prepost_period2
{txt}
{com}. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep i.period2 if period2 != ., absorb(table_code_electionspecific) cluster(table_code_electionspecific)
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 4.period2 omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       448
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}    111{txt}){col 67}= {res}   1047.86
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9384
{txt}{col 51}Adj R-squared{col 67}= {res}    0.9171
{txt}{col 51}Within R-sq.{col 67}= {res}    0.9318
{txt}{col 1}Number of clusters ({res}table_code_electionspecific{txt}) {col 30}= {res}       112{txt}{col 51}Root MSE{col 67}= {res}    3.3313

{txt}{ralign 78:(Std. err. adjusted for {res:112} clusters in {res:table_code_electionspecific})}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}1.post {c |}{col 14}{res}{space 2}-23.86365{col 26}{space 2} .6058719{col 37}{space 1}  -39.39{col 46}{space 3}0.000{col 54}{space 4}-25.06423{col 67}{space 3}-22.66308
{txt}{space 8}1.ep {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 5}post#ep {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2}-3.747646{col 26}{space 2} .8902995{col 37}{space 1}   -4.21{col 46}{space 3}0.000{col 54}{space 4}-5.511834{col 67}{space 3}-1.983458
{txt}{space 12} {c |}
{space 5}period2 {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-1.809397{col 26}{space 2} .4674134{col 37}{space 1}   -3.87{col 46}{space 3}0.000{col 54}{space 4}-2.735607{col 67}{space 3}-.8831857
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-18.18232{col 26}{space 2} .5013171{col 37}{space 1}  -36.27{col 46}{space 3}0.000{col 54}{space 4}-19.17572{col 67}{space 3}-17.18893
{txt}{space 10}4  {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 12} {c |}
{space 7}_cons {c |}{col 14}{res}{space 2} 46.28808{col 26}{space 2} .3440756{col 37}{space 1}  134.53{col 46}{space 3}0.000{col 54}{space 4} 45.60627{col 67}{space 3} 46.96989
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 29}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}                 Absorbed FE{col 30}{c |} Categories{col 43} - Redundant{col 55}  = Num. Coefs{col 70}{c |}
{res}{col 1}{text}{hline 29}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} table_code_electionspecific{col 30}{c |}{space 1}      112{col 43}{space 1}      112{col 55}{result}{space 1}        0{col 69}{text}*{col 70}{c |}
{res}{col 1}{text}{hline 29}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. est store threeperiods_period2
{txt}
{com}. 
. * Make table
. esttab prepost_period3 threeperiods_period3 prepost_period2 threeperiods_period2 using 03_tables/tabled12.tex, tex se replace mtitles ("2003-2019" "2003-2019" "2004-2019" "2004-2015")  keep (1.post 1.post#1.ep 2.period2 3.period2 2.period3 3.period3) coeflabels (1.post#1.ep "Treatment (absence of booth)" ep "European election" 1.post "2019" 2.period2 "2009-11" 3.period2 "2014-15" 2.period3 "2009-11" 3.period3 "2014-15") star(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * election type fixed effects" "Standard errors are clustered by voting station * election type")
{res}{txt}(output written to {browse  `"03_tables/tabled12.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tabled13.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Generate interactions
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
{txt}(2,957 missing values generated)

{com}. gen cabine_use_cs_dummy = cabine_use * cs_dummy
{txt}(2,960 missing values generated)

{com}. gen cabine_use_vox_dummy = cabine_use * vox_dummy
{txt}(2,960 missing values generated)

{com}. gen cabine_use_up_dummy = cabine_use * podemos_dummy
{txt}(2,960 missing values generated)

{com}. gen cabine_use_psoe_dummy = cabine_use * psoe_dummy
{txt}(2,960 missing values generated)

{com}. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_dummy cabine_use_psoe_dummy ///
> , r

{txt}Linear regression                               Number of obs     = {res}     1,843
                                                {txt}F(11, 1831)       =  {res}     1.66
                                                {txt}Prob > F          = {res}    0.0775
                                                {txt}R-squared         = {res}    0.0097
                                                {txt}Root MSE          =    {res} .30288

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}        uncomfortable{col 23}{c |} Coefficient{col 35}  std. err.{col 47}      t{col 55}   P>|t|{col 63}     [95% con{col 76}f. interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}cabine_use {c |}{col 23}{res}{space 2}-.0328764{col 35}{space 2} .0321041{col 46}{space 1}   -1.02{col 55}{space 3}0.306{col 63}{space 4}-.0958409{col 76}{space 3}  .030088
{txt}{space 13}pp_dummy {c |}{col 23}{res}{space 2}-.0168462{col 35}{space 2} .0307426{col 46}{space 1}   -0.55{col 55}{space 3}0.584{col 63}{space 4}-.0771405{col 76}{space 3} .0434481
{txt}{space 13}cs_dummy {c |}{col 23}{res}{space 2} .0193826{col 35}{space 2} .0400044{col 46}{space 1}    0.48{col 55}{space 3}0.628{col 63}{space 4}-.0590766{col 76}{space 3} .0978417
{txt}{space 12}vox_dummy {c |}{col 23}{res}{space 2}-.0044077{col 35}{space 2} .0316282{col 46}{space 1}   -0.14{col 55}{space 3}0.889{col 63}{space 4}-.0664388{col 76}{space 3} .0576233
{txt}{space 8}podemos_dummy {c |}{col 23}{res}{space 2}-.0012255{col 35}{space 2} .0282516{col 46}{space 1}   -0.04{col 55}{space 3}0.965{col 63}{space 4}-.0566343{col 76}{space 3} .0541833
{txt}{space 11}psoe_dummy {c |}{col 23}{res}{space 2} .0273205{col 35}{space 2} .0270791{col 46}{space 1}    1.01{col 55}{space 3}0.313{col 63}{space 4}-.0257887{col 76}{space 3} .0804298
{txt}{space 2}cabine_use_pp_dummy {c |}{col 23}{res}{space 2} .1292671{col 35}{space 2} .0516341{col 46}{space 1}    2.50{col 55}{space 3}0.012{col 63}{space 4} .0279992{col 76}{space 3} .2305351
{txt}{space 2}cabine_use_cs_dummy {c |}{col 23}{res}{space 2}-.0216525{col 35}{space 2} .0555296{col 46}{space 1}   -0.39{col 55}{space 3}0.697{col 63}{space 4}-.1305606{col 76}{space 3} .0872555
{txt}{space 1}cabine_use_vox_dummy {c |}{col 23}{res}{space 2} .0710324{col 35}{space 2} .0501891{col 46}{space 1}    1.42{col 55}{space 3}0.157{col 63}{space 4}-.0274015{col 76}{space 3} .1694664
{txt}{space 2}cabine_use_up_dummy {c |}{col 23}{res}{space 2}-.0026774{col 35}{space 2} .0431456{col 46}{space 1}   -0.06{col 55}{space 3}0.951{col 63}{space 4}-.0872972{col 76}{space 3} .0819424
{txt}cabine_use_psoe_dummy {c |}{col 23}{res}{space 2}  .029374{col 35}{space 2} .0428827{col 46}{space 1}    0.68{col 55}{space 3}0.493{col 63}{space 4}-.0547302{col 76}{space 3} .1134781
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} .0931174{col 35}{space 2} .0185507{col 46}{space 1}    5.02{col 55}{space 3}0.000{col 63}{space 4} .0567346{col 76}{space 3} .1295002
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_nocontrols_all
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. estadd local FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_dummy cabine_use_psoe_dummy ///
> i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,843
                                                {txt}F(29, 1813)       =  {res}     2.96
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0427
                                                {txt}Root MSE          =    {res} .29928

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                uncomfortable{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}cabine_use {c |}{col 31}{res}{space 2}-.0489403{col 43}{space 2} .0338926{col 54}{space 1}   -1.44{col 63}{space 3}0.149{col 71}{space 4}-.1154129{col 84}{space 3} .0175323
{txt}{space 21}pp_dummy {c |}{col 31}{res}{space 2}-.0612672{col 43}{space 2} .0350222{col 54}{space 1}   -1.75{col 63}{space 3}0.080{col 71}{space 4}-.1299552{col 84}{space 3} .0074209
{txt}{space 21}cs_dummy {c |}{col 31}{res}{space 2}-.0176225{col 43}{space 2}  .040701{col 54}{space 1}   -0.43{col 63}{space 3}0.665{col 71}{space 4}-.0974482{col 84}{space 3} .0622032
{txt}{space 20}vox_dummy {c |}{col 31}{res}{space 2}-.0478195{col 43}{space 2} .0361432{col 54}{space 1}   -1.32{col 63}{space 3}0.186{col 71}{space 4}-.1187061{col 84}{space 3} .0230671
{txt}{space 16}podemos_dummy {c |}{col 31}{res}{space 2}-.0470035{col 43}{space 2} .0326646{col 54}{space 1}   -1.44{col 63}{space 3}0.150{col 71}{space 4}-.1110676{col 84}{space 3} .0170607
{txt}{space 19}psoe_dummy {c |}{col 31}{res}{space 2}-.0100323{col 43}{space 2} .0302314{col 54}{space 1}   -0.33{col 63}{space 3}0.740{col 71}{space 4}-.0693243{col 84}{space 3} .0492597
{txt}{space 10}cabine_use_pp_dummy {c |}{col 31}{res}{space 2} .1407423{col 43}{space 2} .0522881{col 54}{space 1}    2.69{col 63}{space 3}0.007{col 71}{space 4} .0381909{col 84}{space 3} .2432936
{txt}{space 10}cabine_use_cs_dummy {c |}{col 31}{res}{space 2}-.0156648{col 43}{space 2} .0564479{col 54}{space 1}   -0.28{col 63}{space 3}0.781{col 71}{space 4}-.1263746{col 84}{space 3}  .095045
{txt}{space 9}cabine_use_vox_dummy {c |}{col 31}{res}{space 2}  .079997{col 43}{space 2} .0512018{col 54}{space 1}    1.56{col 63}{space 3}0.118{col 71}{space 4}-.0204237{col 84}{space 3} .1804178
{txt}{space 10}cabine_use_up_dummy {c |}{col 31}{res}{space 2} .0244346{col 43}{space 2} .0444438{col 54}{space 1}    0.55{col 63}{space 3}0.583{col 71}{space 4}-.0627318{col 84}{space 3} .1116011
{txt}{space 8}cabine_use_psoe_dummy {c |}{col 31}{res}{space 2} .0468537{col 43}{space 2} .0432227{col 54}{space 1}    1.08{col 63}{space 3}0.279{col 71}{space 4}-.0379178{col 84}{space 3} .1316253
{txt}{space 29} {c |}
{space 25}CCAA {c |}
{space 22}Aragón  {c |}{col 31}{res}{space 2}-.0280734{col 43}{space 2} .0394129{col 54}{space 1}   -0.71{col 63}{space 3}0.476{col 71}{space 4}-.1053729{col 84}{space 3}  .049226
{txt}{space 4}Asturias (Principado de)  {c |}{col 31}{res}{space 2} .0946948{col 43}{space 2} .0555969{col 54}{space 1}    1.70{col 63}{space 3}0.089{col 71}{space 4}-.0143459{col 84}{space 3} .2037355
{txt}{space 13}Balears (Illes)  {c |}{col 31}{res}{space 2} .0091112{col 43}{space 2} .0428504{col 54}{space 1}    0.21{col 63}{space 3}0.832{col 71}{space 4}-.0749301{col 84}{space 3} .0931526
{txt}{space 20}Canarias  {c |}{col 31}{res}{space 2}-.0523523{col 43}{space 2} .0387483{col 54}{space 1}   -1.35{col 63}{space 3}0.177{col 71}{space 4}-.1283483{col 84}{space 3} .0236437
{txt}{space 19}Cantabria  {c |}{col 31}{res}{space 2}-.0306788{col 43}{space 2} .0378104{col 54}{space 1}   -0.81{col 63}{space 3}0.417{col 71}{space 4}-.1048353{col 84}{space 3} .0434777
{txt}{space 10}Castilla-La Mancha  {c |}{col 31}{res}{space 2} .1298005{col 43}{space 2} .0586363{col 54}{space 1}    2.21{col 63}{space 3}0.027{col 71}{space 4} .0147987{col 84}{space 3} .2448023
{txt}{space 13}Castilla y León  {c |}{col 31}{res}{space 2} .0926454{col 43}{space 2} .0507302{col 54}{space 1}    1.83{col 63}{space 3}0.068{col 71}{space 4}-.0068503{col 84}{space 3} .1921411
{txt}{space 20}Cataluña  {c |}{col 31}{res}{space 2}-.0714654{col 43}{space 2} .0290897{col 54}{space 1}   -2.46{col 63}{space 3}0.014{col 71}{space 4}-.1285182{col 84}{space 3}-.0144126
{txt}{space 8}Comunitat Valenciana  {c |}{col 31}{res}{space 2}-.0840916{col 43}{space 2} .0252205{col 54}{space 1}   -3.33{col 63}{space 3}0.001{col 71}{space 4}-.1335559{col 84}{space 3}-.0346273
{txt}{space 17}Extremadura  {c |}{col 31}{res}{space 2}-.0232545{col 43}{space 2}  .040442{col 54}{space 1}   -0.58{col 63}{space 3}0.565{col 71}{space 4}-.1025723{col 84}{space 3} .0560632
{txt}{space 21}Galicia  {c |}{col 31}{res}{space 2}-.0541703{col 43}{space 2} .0330914{col 54}{space 1}   -1.64{col 63}{space 3}0.102{col 71}{space 4}-.1190716{col 84}{space 3}  .010731
{txt}{space 7}Madrid (Comunidad de)  {c |}{col 31}{res}{space 2} .0010469{col 43}{space 2} .0300927{col 54}{space 1}    0.03{col 63}{space 3}0.972{col 71}{space 4} -.057973{col 84}{space 3} .0600669
{txt}{space 10}Murcia (Región de)  {c |}{col 31}{res}{space 2}-.1096253{col 43}{space 2} .0247846{col 54}{space 1}   -4.42{col 63}{space 3}0.000{col 71}{space 4}-.1582348{col 84}{space 3}-.0610159
{txt}Navarra (Comunidad Foral de)  {c |}{col 31}{res}{space 2} .0300629{col 43}{space 2} .0601866{col 54}{space 1}    0.50{col 63}{space 3}0.617{col 71}{space 4}-.0879795{col 84}{space 3} .1481052
{txt}{space 18}País Vasco  {c |}{col 31}{res}{space 2}-.0886425{col 43}{space 2} .0315086{col 54}{space 1}   -2.81{col 63}{space 3}0.005{col 71}{space 4}-.1504395{col 84}{space 3}-.0268455
{txt}{space 18}Rioja (La)  {c |}{col 31}{res}{space 2} -.039622{col 43}{space 2} .0409641{col 54}{space 1}   -0.97{col 63}{space 3}0.334{col 71}{space 4}-.1199638{col 84}{space 3} .0407197
{txt}{space 2}Ceuta (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .0360174{col 43}{space 2} .0672291{col 54}{space 1}    0.54{col 63}{space 3}0.592{col 71}{space 4}-.0958372{col 84}{space 3}  .167872
{txt}Melilla (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2}-.0779776{col 43}{space 2}  .065413{col 54}{space 1}   -1.19{col 63}{space 3}0.233{col 71}{space 4}-.2062704{col 84}{space 3} .0503151
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2}  .147763{col 43}{space 2} .0319257{col 54}{space 1}    4.63{col 63}{space 3}0.000{col 71}{space 4}  .085148{col 84}{space 3}  .210378
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_fe_all
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. estadd local FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_dummy cabine_use_psoe_dummy ///
> female i.income i.TAMUNI age age_sq i.education, r

{txt}Linear regression                               Number of obs     = {res}     1,352
                                                {txt}F(35, 1316)       =  {res}     2.35
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0397
                                                {txt}Root MSE          =    {res} .28459

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2} -.062219{col 45}{space 2} .0365038{col 56}{space 1}   -1.70{col 65}{space 3}0.089{col 73}{space 4} -.133831{col 86}{space 3}  .009393
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2} -.039187{col 45}{space 2} .0375896{col 56}{space 1}   -1.04{col 65}{space 3}0.297{col 73}{space 4} -.112929{col 86}{space 3} .0345551
{txt}{space 23}cs_dummy {c |}{col 33}{res}{space 2} .0207302{col 45}{space 2} .0501177{col 56}{space 1}    0.41{col 65}{space 3}0.679{col 73}{space 4}-.0775891{col 86}{space 3} .1190494
{txt}{space 22}vox_dummy {c |}{col 33}{res}{space 2}-.0076771{col 45}{space 2} .0403518{col 56}{space 1}   -0.19{col 65}{space 3}0.849{col 73}{space 4}-.0868381{col 86}{space 3} .0714838
{txt}{space 18}podemos_dummy {c |}{col 33}{res}{space 2}-.0098559{col 45}{space 2} .0350708{col 56}{space 1}   -0.28{col 65}{space 3}0.779{col 73}{space 4}-.0786567{col 86}{space 3}  .058945
{txt}{space 21}psoe_dummy {c |}{col 33}{res}{space 2}-.0047778{col 45}{space 2} .0331048{col 56}{space 1}   -0.14{col 65}{space 3}0.885{col 73}{space 4}-.0697217{col 86}{space 3} .0601661
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2}  .146309{col 45}{space 2} .0573508{col 56}{space 1}    2.55{col 65}{space 3}0.011{col 73}{space 4}    .0338{col 86}{space 3} .2588179
{txt}{space 12}cabine_use_cs_dummy {c |}{col 33}{res}{space 2}-.0390384{col 45}{space 2} .0607741{col 56}{space 1}   -0.64{col 65}{space 3}0.521{col 73}{space 4}-.1582631{col 86}{space 3} .0801862
{txt}{space 11}cabine_use_vox_dummy {c |}{col 33}{res}{space 2} .0550807{col 45}{space 2}  .056247{col 56}{space 1}    0.98{col 65}{space 3}0.328{col 73}{space 4}-.0552629{col 86}{space 3} .1654242
{txt}{space 12}cabine_use_up_dummy {c |}{col 33}{res}{space 2} .0192804{col 45}{space 2} .0475354{col 56}{space 1}    0.41{col 65}{space 3}0.685{col 73}{space 4}-.0739731{col 86}{space 3} .1125339
{txt}{space 10}cabine_use_psoe_dummy {c |}{col 33}{res}{space 2} .0509321{col 45}{space 2} .0477899{col 56}{space 1}    1.07{col 65}{space 3}0.287{col 73}{space 4}-.0428205{col 86}{space 3} .1446848
{txt}{space 25}female {c |}{col 33}{res}{space 2}  .030037{col 45}{space 2} .0161056{col 56}{space 1}    1.87{col 65}{space 3}0.062{col 73}{space 4}-.0015584{col 86}{space 3} .0616324
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0286401{col 45}{space 2} .0643067{col 56}{space 1}    0.45{col 65}{space 3}0.656{col 73}{space 4}-.0975146{col 86}{space 3} .1547949
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0692304{col 45}{space 2} .0415771{col 56}{space 1}    1.67{col 65}{space 3}0.096{col 73}{space 4}-.0123342{col 86}{space 3} .1507951
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0069631{col 45}{space 2} .0309496{col 56}{space 1}    0.22{col 65}{space 3}0.822{col 73}{space 4}-.0537529{col 86}{space 3}  .067679
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0153031{col 45}{space 2} .0292933{col 56}{space 1}    0.52{col 65}{space 3}0.601{col 73}{space 4}-.0421635{col 86}{space 3} .0727697
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0131808{col 45}{space 2}  .027731{col 56}{space 1}    0.48{col 65}{space 3}0.635{col 73}{space 4}-.0412209{col 86}{space 3} .0675825
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0352307{col 45}{space 2} .0291083{col 56}{space 1}   -1.21{col 65}{space 3}0.226{col 73}{space 4}-.0923345{col 86}{space 3}  .021873
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0176084{col 45}{space 2} .0424095{col 56}{space 1}   -0.42{col 65}{space 3}0.678{col 73}{space 4} -.100806{col 86}{space 3} .0655892
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0746578{col 45}{space 2} .0705705{col 56}{space 1}    1.06{col 65}{space 3}0.290{col 73}{space 4}-.0637852{col 86}{space 3} .2131008
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0868425{col 45}{space 2} .0402415{col 56}{space 1}   -2.16{col 65}{space 3}0.031{col 73}{space 4}-.1657871{col 86}{space 3}-.0078979
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0816489{col 45}{space 2}  .033045{col 56}{space 1}   -2.47{col 65}{space 3}0.014{col 73}{space 4}-.1464755{col 86}{space 3}-.0168222
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0596707{col 45}{space 2} .0376816{col 56}{space 1}    1.58{col 65}{space 3}0.114{col 73}{space 4} -.014252{col 86}{space 3} .1335933
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0188846{col 45}{space 2} .0325376{col 56}{space 1}    0.58{col 65}{space 3}0.562{col 73}{space 4}-.0449466{col 86}{space 3} .0827158
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .033204{col 45}{space 2} .0371568{col 56}{space 1}    0.89{col 65}{space 3}0.372{col 73}{space 4} -.039689{col 86}{space 3}  .106097
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0027686{col 45}{space 2}  .032824{col 56}{space 1}    0.08{col 65}{space 3}0.933{col 73}{space 4}-.0616246{col 86}{space 3} .0671617
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0507011{col 45}{space 2} .0326853{col 56}{space 1}   -1.55{col 65}{space 3}0.121{col 73}{space 4}-.1148221{col 86}{space 3}   .01342
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0459459{col 45}{space 2} .0366469{col 56}{space 1}   -1.25{col 65}{space 3}0.210{col 73}{space 4}-.1178386{col 86}{space 3} .0259468
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0021501{col 45}{space 2} .0031799{col 56}{space 1}   -0.68{col 65}{space 3}0.499{col 73}{space 4}-.0083884{col 86}{space 3} .0040881
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000251{col 45}{space 2} .0000336{col 56}{space 1}    0.75{col 65}{space 3}0.456{col 73}{space 4}-.0000409{col 86}{space 3} .0000911
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0787254{col 45}{space 2} .0910407{col 56}{space 1}   -0.86{col 65}{space 3}0.387{col 73}{space 4}-.2573261{col 86}{space 3} .0998753
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0436379{col 45}{space 2} .0923753{col 56}{space 1}   -0.47{col 65}{space 3}0.637{col 73}{space 4}-.2248568{col 86}{space 3}  .137581
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0893426{col 45}{space 2} .0924903{col 56}{space 1}   -0.97{col 65}{space 3}0.334{col 73}{space 4}-.2707872{col 86}{space 3}  .092102
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0817001{col 45}{space 2}  .092268{col 56}{space 1}   -0.89{col 65}{space 3}0.376{col 73}{space 4}-.2627085{col 86}{space 3} .0993083
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} -.072853{col 45}{space 2} .0924837{col 56}{space 1}   -0.79{col 65}{space 3}0.431{col 73}{space 4}-.2542846{col 86}{space 3} .1085786
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1806946{col 45}{space 2} .1104606{col 56}{space 1}    1.64{col 65}{space 3}0.102{col 73}{space 4}-.0360034{col 86}{space 3} .3973927
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_controls_all
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. estadd local FE "No"

{txt}added macro:
                 e(FE) : "{res:No}"

{com}. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_dummy cabine_use_psoe_dummy ///
> female i.income i.TAMUNI age age_sq i.education i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,352
                                                {txt}F(53, 1298)       =  {res}     2.03
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0809
                                                {txt}Root MSE          =    {res} .28035

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0524849{col 45}{space 2} .0369894{col 56}{space 1}   -1.42{col 65}{space 3}0.156{col 73}{space 4}-.1250504{col 86}{space 3} .0200806
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0591206{col 45}{space 2} .0397095{col 56}{space 1}   -1.49{col 65}{space 3}0.137{col 73}{space 4}-.1370225{col 86}{space 3} .0187812
{txt}{space 23}cs_dummy {c |}{col 33}{res}{space 2}-.0005045{col 45}{space 2} .0491396{col 56}{space 1}   -0.01{col 65}{space 3}0.992{col 73}{space 4}-.0969062{col 86}{space 3} .0958973
{txt}{space 22}vox_dummy {c |}{col 33}{res}{space 2} -.029682{col 45}{space 2} .0437098{col 56}{space 1}   -0.68{col 65}{space 3}0.497{col 73}{space 4}-.1154315{col 86}{space 3} .0560676
{txt}{space 18}podemos_dummy {c |}{col 33}{res}{space 2}-.0296962{col 45}{space 2}  .036813{col 56}{space 1}   -0.81{col 65}{space 3}0.420{col 73}{space 4}-.1019156{col 86}{space 3} .0425233
{txt}{space 21}psoe_dummy {c |}{col 33}{res}{space 2}-.0230886{col 45}{space 2} .0355828{col 56}{space 1}   -0.65{col 65}{space 3}0.517{col 73}{space 4}-.0928947{col 86}{space 3} .0467176
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1431965{col 45}{space 2} .0565183{col 56}{space 1}    2.53{col 65}{space 3}0.011{col 73}{space 4} .0323193{col 86}{space 3} .2540737
{txt}{space 12}cabine_use_cs_dummy {c |}{col 33}{res}{space 2}-.0391424{col 45}{space 2} .0615312{col 56}{space 1}   -0.64{col 65}{space 3}0.525{col 73}{space 4} -.159854{col 86}{space 3} .0815691
{txt}{space 11}cabine_use_vox_dummy {c |}{col 33}{res}{space 2} .0517806{col 45}{space 2}  .056467{col 56}{space 1}    0.92{col 65}{space 3}0.359{col 73}{space 4} -.058996{col 86}{space 3} .1625573
{txt}{space 12}cabine_use_up_dummy {c |}{col 33}{res}{space 2} .0334828{col 45}{space 2} .0482393{col 56}{space 1}    0.69{col 65}{space 3}0.488{col 73}{space 4}-.0611528{col 86}{space 3} .1281184
{txt}{space 10}cabine_use_psoe_dummy {c |}{col 33}{res}{space 2} .0663712{col 45}{space 2} .0482773{col 56}{space 1}    1.37{col 65}{space 3}0.169{col 73}{space 4}-.0283389{col 86}{space 3} .1610814
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0293904{col 45}{space 2} .0158499{col 56}{space 1}    1.85{col 65}{space 3}0.064{col 73}{space 4}-.0017038{col 86}{space 3} .0604845
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0235038{col 45}{space 2} .0650166{col 56}{space 1}    0.36{col 65}{space 3}0.718{col 73}{space 4}-.1040453{col 86}{space 3}  .151053
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0821234{col 45}{space 2} .0407727{col 56}{space 1}    2.01{col 65}{space 3}0.044{col 73}{space 4} .0021357{col 86}{space 3} .1621111
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0115922{col 45}{space 2} .0306008{col 56}{space 1}    0.38{col 65}{space 3}0.705{col 73}{space 4}-.0484402{col 86}{space 3} .0716247
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0123337{col 45}{space 2} .0281737{col 56}{space 1}    0.44{col 65}{space 3}0.662{col 73}{space 4}-.0429373{col 86}{space 3} .0676046
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0089293{col 45}{space 2} .0279396{col 56}{space 1}    0.32{col 65}{space 3}0.749{col 73}{space 4}-.0458824{col 86}{space 3} .0637411
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0351712{col 45}{space 2} .0301679{col 56}{space 1}   -1.17{col 65}{space 3}0.244{col 73}{space 4}-.0943544{col 86}{space 3}  .024012
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0290018{col 45}{space 2} .0424282{col 56}{space 1}   -0.68{col 65}{space 3}0.494{col 73}{space 4}-.1122371{col 86}{space 3} .0542336
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0717086{col 45}{space 2} .0666299{col 56}{space 1}    1.08{col 65}{space 3}0.282{col 73}{space 4}-.0590055{col 86}{space 3} .2024228
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0789769{col 45}{space 2} .0551248{col 56}{space 1}   -1.43{col 65}{space 3}0.152{col 73}{space 4}-.1871204{col 86}{space 3} .0291665
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0829373{col 45}{space 2} .0408216{col 56}{space 1}   -2.03{col 65}{space 3}0.042{col 73}{space 4}-.1630208{col 86}{space 3}-.0028538
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0534677{col 45}{space 2} .0373177{col 56}{space 1}    1.43{col 65}{space 3}0.152{col 73}{space 4} -.019742{col 86}{space 3} .1266774
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0212313{col 45}{space 2} .0325786{col 56}{space 1}    0.65{col 65}{space 3}0.515{col 73}{space 4}-.0426811{col 86}{space 3} .0851437
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .004822{col 45}{space 2} .0378757{col 56}{space 1}    0.13{col 65}{space 3}0.899{col 73}{space 4}-.0694823{col 86}{space 3} .0791263
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0086619{col 45}{space 2} .0337595{col 56}{space 1}   -0.26{col 65}{space 3}0.798{col 73}{space 4}-.0748911{col 86}{space 3} .0575674
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0364614{col 45}{space 2} .0366793{col 56}{space 1}   -0.99{col 65}{space 3}0.320{col 73}{space 4}-.1084186{col 86}{space 3} .0354958
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1061079{col 45}{space 2} .0428795{col 56}{space 1}   -2.47{col 65}{space 3}0.013{col 73}{space 4}-.1902287{col 86}{space 3}-.0219872
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0011929{col 45}{space 2} .0031376{col 56}{space 1}   -0.38{col 65}{space 3}0.704{col 73}{space 4}-.0073483{col 86}{space 3} .0049626
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000164{col 45}{space 2} .0000332{col 56}{space 1}    0.49{col 65}{space 3}0.622{col 73}{space 4}-.0000488{col 86}{space 3} .0000816
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0709753{col 45}{space 2}  .092939{col 56}{space 1}   -0.76{col 65}{space 3}0.445{col 73}{space 4}-.2533024{col 86}{space 3} .1113518
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0327749{col 45}{space 2} .0953002{col 56}{space 1}   -0.34{col 65}{space 3}0.731{col 73}{space 4}-.2197341{col 86}{space 3} .1541844
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0808576{col 45}{space 2} .0955263{col 56}{space 1}   -0.85{col 65}{space 3}0.397{col 73}{space 4}-.2682605{col 86}{space 3} .1065453
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0693122{col 45}{space 2} .0952458{col 56}{space 1}   -0.73{col 65}{space 3}0.467{col 73}{space 4}-.2561647{col 86}{space 3} .1175403
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0632318{col 45}{space 2} .0956643{col 56}{space 1}   -0.66{col 65}{space 3}0.509{col 73}{space 4}-.2509055{col 86}{space 3} .1244418
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} -.023663{col 45}{space 2} .0368071{col 56}{space 1}   -0.64{col 65}{space 3}0.520{col 73}{space 4}-.0958709{col 86}{space 3} .0485449
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0626174{col 45}{space 2} .0550818{col 56}{space 1}    1.14{col 65}{space 3}0.256{col 73}{space 4}-.0454417{col 86}{space 3} .1706765
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0517605{col 45}{space 2}  .051799{col 56}{space 1}    1.00{col 65}{space 3}0.318{col 73}{space 4}-.0498585{col 86}{space 3} .1533794
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0560818{col 45}{space 2} .0344789{col 56}{space 1}   -1.63{col 65}{space 3}0.104{col 73}{space 4}-.1237223{col 86}{space 3} .0115587
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0346803{col 45}{space 2} .0372351{col 56}{space 1}   -0.93{col 65}{space 3}0.352{col 73}{space 4}-.1077279{col 86}{space 3} .0383673
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1316834{col 45}{space 2} .0605627{col 56}{space 1}    2.17{col 65}{space 3}0.030{col 73}{space 4}  .012872{col 86}{space 3} .2504949
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0864184{col 45}{space 2} .0553725{col 56}{space 1}    1.56{col 65}{space 3}0.119{col 73}{space 4} -.022211{col 86}{space 3} .1950478
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0007122{col 45}{space 2} .0372707{col 56}{space 1}   -0.02{col 65}{space 3}0.985{col 73}{space 4}-.0738295{col 86}{space 3} .0724051
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0545316{col 45}{space 2} .0281097{col 56}{space 1}   -1.94{col 65}{space 3}0.053{col 73}{space 4} -.109677{col 86}{space 3} .0006138
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} -.016347{col 45}{space 2} .0436031{col 56}{space 1}   -0.37{col 65}{space 3}0.708{col 73}{space 4}-.1018872{col 86}{space 3} .0691933
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0941473{col 45}{space 2} .0288171{col 56}{space 1}   -3.27{col 65}{space 3}0.001{col 73}{space 4}-.1506804{col 86}{space 3}-.0376142
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}  .100575{col 45}{space 2} .0419995{col 56}{space 1}    2.39{col 65}{space 3}0.017{col 73}{space 4} .0181807{col 86}{space 3} .1829694
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0658899{col 45}{space 2} .0258598{col 56}{space 1}   -2.55{col 65}{space 3}0.011{col 73}{space 4}-.1166215{col 86}{space 3}-.0151584
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0185987{col 45}{space 2} .0589216{col 56}{space 1}   -0.32{col 65}{space 3}0.752{col 73}{space 4}-.1341907{col 86}{space 3} .0969933
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0634331{col 45}{space 2} .0371961{col 56}{space 1}   -1.71{col 65}{space 3}0.088{col 73}{space 4}-.1364041{col 86}{space 3} .0095379
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0896216{col 45}{space 2}  .026442{col 56}{space 1}   -3.39{col 65}{space 3}0.001{col 73}{space 4}-.1414953{col 86}{space 3}-.0377479
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0911016{col 45}{space 2} .0824632{col 56}{space 1}    1.10{col 65}{space 3}0.269{col 73}{space 4} -.070674{col 86}{space 3} .2528773
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0342286{col 45}{space 2} .0662299{col 56}{space 1}   -0.52{col 65}{space 3}0.605{col 73}{space 4} -.164158{col 86}{space 3} .0957008
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1627692{col 45}{space 2} .1165019{col 56}{space 1}    1.40{col 65}{space 3}0.163{col 73}{space 4}-.0657836{col 86}{space 3} .3913219
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_fe_controls_all
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. estadd local FE "Yes"

{txt}added macro:
                 e(FE) : "{res:Yes}"

{com}. 
. 
. * Make table
. esttab uncomf_nocontrols_all uncomf_controls_all uncomf_fe_all uncomf_fe_controls_all using 03_tables/tabled13.tex, tex se replace  keep (cabine_use pp_dummy cabine_use_pp_dummy cs_dummy cabine_use_cs_dummy vox_dummy cabine_use_vox_dummy podemos_dummy cabine_use_up_dummy psoe_dummy cabine_use_psoe_dummy) coeflabels (cabine_use "Used a booth to vote" pp_dummy "Voted for PP" cabine_use_pp_dummy "Used booth x voted PP" cs_dummy "Voted for Ciudadanos" cabine_use_cs_dummy "Used booth x voted Ciudadanos" vox_dummy "Voted for Vox" cabine_use_vox_dummy "Used booth x voted Vox" podemos_dummy "Voted for Podemos" cabine_use_up_dummy "Used booth x voted Podemos" psoe_dummy "Voted for PSOE" cabine_use_psoe_dummy "Used booth x voted PSOE" ) star(* 0.10 ** 0.05 *** 0.01) s(Controls FE, label("Controls" "Region fixed effects")) nomtitles addnotes("Standard errors are robust" "The outcome variable is a dummy for whether each respondent showed" "signs of discomfort during the survey interview" "Models 2 and 4 include controls for income, education, age, age squared, size of" "respondent's municipality, and a dummy for respondents identifying as female") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/tabled13.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tablee1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. regr pp_voteshare post##ciutadella if period > 1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}   150,634
{txt}{hline 13}{c +}{hline 34}   F(3, 150630)    = {res}  2506.40
{txt}       Model {c |} {res} 1497568.11         3  499189.371   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 30000312.2   150,630  199.165586   {txt}R-squared       ={res}    0.0475
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0475
{txt}       Total {c |} {res} 31497880.3   150,633  209.103452   {txt}Root MSE        =   {res} 14.113

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   pp_voteshare{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.post {c |}{col 17}{res}{space 2} -6.32347{col 29}{space 2} .0729537{col 40}{space 1}  -86.68{col 49}{space 3}0.000{col 57}{space 4}-6.466458{col 70}{space 3}-6.180482
{txt}{space 3}1.ciutadella {c |}{col 17}{res}{space 2} .4739284{col 29}{space 2} 1.886634{col 40}{space 1}    0.25{col 49}{space 3}0.802{col 57}{space 4}-3.223836{col 70}{space 3} 4.171693
{txt}{space 15} {c |}
post#ciutadella {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}-.1831933{col 29}{space 2} 2.668029{col 40}{space 1}   -0.07{col 49}{space 3}0.945{col 57}{space 4}-5.412476{col 70}{space 3} 5.046089
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 27.20169{col 29}{space 2} .0534745{col 40}{space 1}  508.69{col 49}{space 3}0.000{col 57}{space 4} 27.09688{col 70}{space 3}  27.3065
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store reverse_bandwagon_1
{txt}
{com}. 
. regr pp_voteshare post##ciutadella

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}   231,289
{txt}{hline 13}{c +}{hline 34}   F(3, 231285)    = {res} 12546.69
{txt}       Model {c |} {res} 10114451.4         3  3371483.81   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 62149744.6   231,285  268.714982   {txt}R-squared       ={res}    0.1400
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1400
{txt}       Total {c |} {res} 72264196.1   231,288  312.442479   {txt}Root MSE        =   {res} 16.393

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   pp_voteshare{col 17}{c |} Coefficient{col 29}  Std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}1.post {c |}{col 17}{res}{space 2}-13.86503{col 29}{space 2} .0714925{col 40}{space 1} -193.94{col 49}{space 3}0.000{col 57}{space 4}-14.00515{col 70}{space 3}-13.72491
{txt}{space 3}1.ciutadella {c |}{col 17}{res}{space 2} .6820743{col 29}{space 2} 1.549526{col 40}{space 1}    0.44{col 49}{space 3}0.660{col 57}{space 4}-2.354956{col 70}{space 3} 3.719104
{txt}{space 15} {c |}
post#ciutadella {c |}
{space 11}1 1  {c |}{col 17}{res}{space 2}-.3913392{col 29}{space 2}  2.68381{col 40}{space 1}   -0.15{col 49}{space 3}0.884{col 57}{space 4}-5.651537{col 70}{space 3} 4.868858
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 34.74325{col 29}{space 2} .0422902{col 40}{space 1}  821.54{col 49}{space 3}0.000{col 57}{space 4} 34.66037{col 70}{space 3} 34.82614
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store reverse_bandwagon_2
{txt}
{com}. 
. * Make table
. esttab reverse_bandwagon_1 reverse_bandwagon_2 using 03_tables/tablee1.tex, tex se replace mtitles ("2014-2019" "2009-2019") keep(_cons 1.post 1.ciutadella 1.post#1.ciutadella) coeflabels (_cons "Constant" 1.post "2019" 1.ciutadella "Ciutadella" 1.post#1.ciutadella "2019 x Ciutadella") star(* 0.10 ** 0.05 *** 0.01)
{res}{txt}(output written to {browse  `"03_tables/tablee1.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Local with outcomes
. local outcomes had_doubts voted_conviction vote_decision_long_ago vote_loyalty 
{txt}
{com}. 
. * Loop over these outcomes and run regressions
. foreach outcome in `outcomes'{c -(}
{txt}  2{com}.         regr `outcome' pp_dummy female i.income age age_sq i.education i.TAMUNI i.CCAA, r
{txt}  3{com}.         est store wp_`outcome'
{txt}  4{com}. {c )-}

{txt}Linear regression                               Number of obs     = {res}     2,479
                                                {txt}{help j_robustsingular:F(43, 2434) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.1027
                                                {txt}Root MSE          =    {res} .40052

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     had_doubts{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0164605{col 45}{space 2} .0205972{col 56}{space 1}   -0.80{col 65}{space 3}0.424{col 73}{space 4}-.0568502{col 86}{space 3} .0239293
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0218251{col 45}{space 2} .0180055{col 56}{space 1}    1.21{col 65}{space 3}0.226{col 73}{space 4}-.0134826{col 86}{space 3} .0571327
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0237723{col 45}{space 2} .0604133{col 56}{space 1}    0.39{col 65}{space 3}0.694{col 73}{space 4}-.0946945{col 86}{space 3}  .142239
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .001571{col 45}{space 2} .0341204{col 56}{space 1}    0.05{col 65}{space 3}0.963{col 73}{space 4}-.0653371{col 86}{space 3} .0684791
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0034163{col 45}{space 2} .0280103{col 56}{space 1}   -0.12{col 65}{space 3}0.903{col 73}{space 4}-.0583427{col 86}{space 3} .0515101
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0182813{col 45}{space 2} .0275426{col 56}{space 1}   -0.66{col 65}{space 3}0.507{col 73}{space 4}-.0722908{col 86}{space 3} .0357281
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0382805{col 45}{space 2} .0307751{col 56}{space 1}    1.24{col 65}{space 3}0.214{col 73}{space 4}-.0220675{col 86}{space 3} .0986286
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0001234{col 45}{space 2} .0396079{col 56}{space 1}    0.00{col 65}{space 3}0.998{col 73}{space 4}-.0775453{col 86}{space 3} .0777921
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} -.047524{col 45}{space 2} .0544041{col 56}{space 1}   -0.87{col 65}{space 3}0.382{col 73}{space 4}-.1542071{col 86}{space 3} .0591592
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}  .039149{col 45}{space 2} .0779334{col 56}{space 1}    0.50{col 65}{space 3}0.615{col 73}{space 4}-.1136736{col 86}{space 3} .1919716
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.3415427{col 45}{space 2} .0562504{col 56}{space 1}   -6.07{col 65}{space 3}0.000{col 73}{space 4}-.4518463{col 86}{space 3} -.231239
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.2525288{col 45}{space 2} .0520269{col 56}{space 1}   -4.85{col 65}{space 3}0.000{col 73}{space 4}-.3545503{col 86}{space 3}-.1505072
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0043537{col 45}{space 2} .0025972{col 56}{space 1}   -1.68{col 65}{space 3}0.094{col 73}{space 4}-.0094466{col 86}{space 3} .0007392
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-4.18e-06{col 45}{space 2} .0000241{col 56}{space 1}   -0.17{col 65}{space 3}0.862{col 73}{space 4}-.0000514{col 86}{space 3}  .000043
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0115928{col 45}{space 2} .0314286{col 56}{space 1}   -0.37{col 65}{space 3}0.712{col 73}{space 4}-.0732224{col 86}{space 3} .0500367
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0091012{col 45}{space 2} .0361477{col 56}{space 1}   -0.25{col 65}{space 3}0.801{col 73}{space 4}-.0799846{col 86}{space 3} .0617822
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} .0171056{col 45}{space 2} .0403881{col 56}{space 1}    0.42{col 65}{space 3}0.672{col 73}{space 4}-.0620931{col 86}{space 3} .0963042
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} .0011098{col 45}{space 2} .0391972{col 56}{space 1}    0.03{col 65}{space 3}0.977{col 73}{space 4}-.0757535{col 86}{space 3}  .077973
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} .1233506{col 45}{space 2} .0416366{col 56}{space 1}    2.96{col 65}{space 3}0.003{col 73}{space 4} .0417037{col 86}{space 3} .2049975
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2} .9258974{col 45}{space 2} .0614611{col 56}{space 1}   15.06{col 65}{space 3}0.000{col 73}{space 4} .8053759{col 86}{space 3} 1.046419
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0008124{col 45}{space 2} .0313616{col 56}{space 1}   -0.03{col 65}{space 3}0.979{col 73}{space 4}-.0623105{col 86}{space 3} .0606857
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0503196{col 45}{space 2} .0315438{col 56}{space 1}    1.60{col 65}{space 3}0.111{col 73}{space 4}-.0115358{col 86}{space 3}  .112175
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0475778{col 45}{space 2} .0371208{col 56}{space 1}    1.28{col 65}{space 3}0.200{col 73}{space 4}-.0252138{col 86}{space 3} .1203695
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0496361{col 45}{space 2} .0334221{col 56}{space 1}    1.49{col 65}{space 3}0.138{col 73}{space 4}-.0159025{col 86}{space 3} .1151747
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} .0599162{col 45}{space 2}  .041998{col 56}{space 1}    1.43{col 65}{space 3}0.154{col 73}{space 4}-.0224394{col 86}{space 3} .1422717
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0023554{col 45}{space 2} .0532891{col 56}{space 1}   -0.04{col 65}{space 3}0.965{col 73}{space 4} -.106852{col 86}{space 3} .1021413
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} .0215624{col 45}{space 2} .0461735{col 56}{space 1}    0.47{col 65}{space 3}0.641{col 73}{space 4}-.0689811{col 86}{space 3} .1121058
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.0314133{col 45}{space 2} .0442218{col 56}{space 1}   -0.71{col 65}{space 3}0.478{col 73}{space 4}-.1181295{col 86}{space 3} .0553029
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.0373255{col 45}{space 2} .0499925{col 56}{space 1}   -0.75{col 65}{space 3}0.455{col 73}{space 4}-.1353578{col 86}{space 3} .0607068
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .0529756{col 45}{space 2} .0493257{col 56}{space 1}    1.07{col 65}{space 3}0.283{col 73}{space 4}-.0437491{col 86}{space 3} .1497002
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0563409{col 45}{space 2} .0375623{col 56}{space 1}   -1.50{col 65}{space 3}0.134{col 73}{space 4}-.1299982{col 86}{space 3} .0173164
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0166506{col 45}{space 2} .0424658{col 56}{space 1}    0.39{col 65}{space 3}0.695{col 73}{space 4}-.0666222{col 86}{space 3} .0999234
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0497715{col 45}{space 2} .0456546{col 56}{space 1}    1.09{col 65}{space 3}0.276{col 73}{space 4}-.0397544{col 86}{space 3} .1392975
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0614686{col 45}{space 2} .0403679{col 56}{space 1}    1.52{col 65}{space 3}0.128{col 73}{space 4}-.0176905{col 86}{space 3} .1406277
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} .0311017{col 45}{space 2} .0351935{col 56}{space 1}    0.88{col 65}{space 3}0.377{col 73}{space 4}-.0379105{col 86}{space 3}  .100114
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .0190076{col 45}{space 2} .0402604{col 56}{space 1}    0.47{col 65}{space 3}0.637{col 73}{space 4}-.0599406{col 86}{space 3} .0979557
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} .0980263{col 45}{space 2} .0422662{col 56}{space 1}    2.32{col 65}{space 3}0.020{col 73}{space 4} .0151449{col 86}{space 3} .1809077
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .1204135{col 45}{space 2} .0419253{col 56}{space 1}    2.87{col 65}{space 3}0.004{col 73}{space 4} .0382007{col 86}{space 3} .2026264
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0041556{col 45}{space 2}  .043323{col 56}{space 1}   -0.10{col 65}{space 3}0.924{col 73}{space 4}-.0891094{col 86}{space 3} .0807981
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2} -.029988{col 45}{space 2} .0489291{col 56}{space 1}   -0.61{col 65}{space 3}0.540{col 73}{space 4}-.1259351{col 86}{space 3}  .065959
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0441743{col 45}{space 2} .0465027{col 56}{space 1}   -0.95{col 65}{space 3}0.342{col 73}{space 4}-.1353632{col 86}{space 3} .0470146
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0910831{col 45}{space 2} .0508003{col 56}{space 1}   -1.79{col 65}{space 3}0.073{col 73}{space 4}-.1906993{col 86}{space 3} .0085331
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0854626{col 45}{space 2} .0684186{col 56}{space 1}   -1.25{col 65}{space 3}0.212{col 73}{space 4}-.2196274{col 86}{space 3} .0487022
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.2239183{col 45}{space 2} .0375352{col 56}{space 1}   -5.97{col 65}{space 3}0.000{col 73}{space 4}-.2975225{col 86}{space 3}-.1503141
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .3661989{col 45}{space 2} .0766732{col 56}{space 1}    4.78{col 65}{space 3}0.000{col 73}{space 4} .2158475{col 86}{space 3} .5165503
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}     2,466
                                                {txt}{help j_robustsingular:F(43, 2421) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0600
                                                {txt}Root MSE          =    {res} .46818

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}               voted_conviction{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} -.013306{col 45}{space 2}  .024929{col 56}{space 1}   -0.53{col 65}{space 3}0.594{col 73}{space 4}-.0621903{col 86}{space 3} .0355782
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0190425{col 45}{space 2} .0204841{col 56}{space 1}   -0.93{col 65}{space 3}0.353{col 73}{space 4}-.0592108{col 86}{space 3} .0211258
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0099266{col 45}{space 2} .0655461{col 56}{space 1}    0.15{col 65}{space 3}0.880{col 73}{space 4}-.1186057{col 86}{space 3} .1384588
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0392797{col 45}{space 2} .0407392{col 56}{space 1}   -0.96{col 65}{space 3}0.335{col 73}{space 4}-.1191671{col 86}{space 3} .0406076
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0043209{col 45}{space 2} .0338037{col 56}{space 1}   -0.13{col 65}{space 3}0.898{col 73}{space 4}-.0706081{col 86}{space 3} .0619664
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0056793{col 45}{space 2} .0330088{col 56}{space 1}   -0.17{col 65}{space 3}0.863{col 73}{space 4}-.0704078{col 86}{space 3} .0590491
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0032857{col 45}{space 2} .0353597{col 56}{space 1}    0.09{col 65}{space 3}0.926{col 73}{space 4}-.0660527{col 86}{space 3}  .072624
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0528061{col 45}{space 2} .0465486{col 56}{space 1}   -1.13{col 65}{space 3}0.257{col 73}{space 4}-.1440853{col 86}{space 3} .0384732
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} .0841241{col 45}{space 2} .0626097{col 56}{space 1}    1.34{col 65}{space 3}0.179{col 73}{space 4}  -.03865{col 86}{space 3} .2068983
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0751515{col 45}{space 2} .0792589{col 56}{space 1}    0.95{col 65}{space 3}0.343{col 73}{space 4}-.0802707{col 86}{space 3} .2305737
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.049858{col 45}{space 2} .2557054{col 56}{space 1}   -0.19{col 65}{space 3}0.845{col 73}{space 4} -.551282{col 86}{space 3}  .451566
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.058128{col 45}{space 2} .1994346{col 56}{space 1}   -0.29{col 65}{space 3}0.771{col 73}{space 4}-.4492081{col 86}{space 3} .3329522
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0042944{col 45}{space 2}  .003045{col 56}{space 1}   -1.41{col 65}{space 3}0.159{col 73}{space 4}-.0102655{col 86}{space 3} .0016767
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000753{col 45}{space 2} .0000289{col 56}{space 1}    2.61{col 65}{space 3}0.009{col 73}{space 4} .0000187{col 86}{space 3} .0001319
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} .0028087{col 45}{space 2} .0454355{col 56}{space 1}    0.06{col 65}{space 3}0.951{col 73}{space 4}-.0862877{col 86}{space 3} .0919051
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} .0041483{col 45}{space 2} .0491077{col 56}{space 1}    0.08{col 65}{space 3}0.933{col 73}{space 4}-.0921492{col 86}{space 3} .1004458
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0549503{col 45}{space 2} .0528057{col 56}{space 1}   -1.04{col 65}{space 3}0.298{col 73}{space 4}-.1584993{col 86}{space 3} .0485986
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0635929{col 45}{space 2} .0522255{col 56}{space 1}   -1.22{col 65}{space 3}0.223{col 73}{space 4}-.1660041{col 86}{space 3} .0388184
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1381458{col 45}{space 2} .0542973{col 56}{space 1}   -2.54{col 65}{space 3}0.011{col 73}{space 4}-.2446198{col 86}{space 3}-.0316718
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2}-.7013853{col 45}{space 2} .0772009{col 56}{space 1}   -9.09{col 65}{space 3}0.000{col 73}{space 4} -.852772{col 86}{space 3}-.5499986
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0353834{col 45}{space 2} .0422972{col 56}{space 1}    0.84{col 65}{space 3}0.403{col 73}{space 4} -.047559{col 86}{space 3} .1183259
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.0187002{col 45}{space 2} .0408764{col 56}{space 1}   -0.46{col 65}{space 3}0.647{col 73}{space 4}-.0988565{col 86}{space 3} .0614562
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0134553{col 45}{space 2} .0471306{col 56}{space 1}    0.29{col 65}{space 3}0.775{col 73}{space 4}-.0789652{col 86}{space 3} .1058758
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0251784{col 45}{space 2} .0422186{col 56}{space 1}   -0.60{col 65}{space 3}0.551{col 73}{space 4}-.1079668{col 86}{space 3} .0576099
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.029713{col 45}{space 2} .0521981{col 56}{space 1}   -0.57{col 65}{space 3}0.569{col 73}{space 4}-.1320706{col 86}{space 3} .0726445
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} .0879347{col 45}{space 2} .0605478{col 56}{space 1}    1.45{col 65}{space 3}0.147{col 73}{space 4}-.0307961{col 86}{space 3} .2066656
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0553867{col 45}{space 2} .0580022{col 56}{space 1}   -0.95{col 65}{space 3}0.340{col 73}{space 4}-.1691258{col 86}{space 3} .0583523
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.0936143{col 45}{space 2} .0546283{col 56}{space 1}   -1.71{col 65}{space 3}0.087{col 73}{space 4}-.2007373{col 86}{space 3} .0135088
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.0320295{col 45}{space 2} .0609332{col 56}{space 1}   -0.53{col 65}{space 3}0.599{col 73}{space 4}-.1515161{col 86}{space 3} .0874572
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .0577642{col 45}{space 2} .0518567{col 56}{space 1}    1.11{col 65}{space 3}0.265{col 73}{space 4} -.043924{col 86}{space 3} .1594523
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2} .0418405{col 45}{space 2} .0468871{col 56}{space 1}    0.89{col 65}{space 3}0.372{col 73}{space 4}-.0501025{col 86}{space 3} .1337835
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} -.045232{col 45}{space 2} .0499211{col 56}{space 1}   -0.91{col 65}{space 3}0.365{col 73}{space 4}-.1431244{col 86}{space 3} .0526605
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}-.1053995{col 45}{space 2} .0523673{col 56}{space 1}   -2.01{col 65}{space 3}0.044{col 73}{space 4}-.2080889{col 86}{space 3}-.0027102
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0419569{col 45}{space 2} .0438174{col 56}{space 1}    0.96{col 65}{space 3}0.338{col 73}{space 4}-.0439666{col 86}{space 3} .1278804
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0836675{col 45}{space 2} .0400837{col 56}{space 1}   -2.09{col 65}{space 3}0.037{col 73}{space 4}-.1622695{col 86}{space 3}-.0050655
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0241119{col 45}{space 2}  .047919{col 56}{space 1}   -0.50{col 65}{space 3}0.615{col 73}{space 4}-.1180783{col 86}{space 3} .0698545
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.1157326{col 45}{space 2} .0494012{col 56}{space 1}   -2.34{col 65}{space 3}0.019{col 73}{space 4}-.2126056{col 86}{space 3}-.0188596
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.0734499{col 45}{space 2} .0461071{col 56}{space 1}   -1.59{col 65}{space 3}0.111{col 73}{space 4}-.1638635{col 86}{space 3} .0169636
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .0479397{col 45}{space 2}  .048651{col 56}{space 1}    0.99{col 65}{space 3}0.325{col 73}{space 4}-.0474622{col 86}{space 3} .1433416
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0273772{col 45}{space 2} .0620778{col 56}{space 1}   -0.44{col 65}{space 3}0.659{col 73}{space 4}-.1491083{col 86}{space 3} .0943539
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}  .031969{col 45}{space 2} .0573418{col 56}{space 1}    0.56{col 65}{space 3}0.577{col 73}{space 4}-.0804751{col 86}{space 3}  .144413
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} .0741935{col 45}{space 2} .0676127{col 56}{space 1}    1.10{col 65}{space 3}0.273{col 73}{space 4}-.0583912{col 86}{space 3} .2067783
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0635093{col 45}{space 2} .0878927{col 56}{space 1}   -0.72{col 65}{space 3}0.470{col 73}{space 4}-.2358619{col 86}{space 3} .1088434
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0911741{col 45}{space 2} .0792009{col 56}{space 1}    1.15{col 65}{space 3}0.250{col 73}{space 4}-.0641344{col 86}{space 3} .2464826
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .7414272{col 45}{space 2} .0919471{col 56}{space 1}    8.06{col 65}{space 3}0.000{col 73}{space 4} .5611241{col 86}{space 3} .9217302
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}     2,483
                                                {txt}{help j_robustsingular:F(43, 2438) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0737
                                                {txt}Root MSE          =    {res}  .8788

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}         vote_decision_long_ago{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0373094{col 45}{space 2} .0450003{col 56}{space 1}    0.83{col 65}{space 3}0.407{col 73}{space 4}-.0509333{col 86}{space 3} .1255521
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0636941{col 45}{space 2} .0392707{col 56}{space 1}   -1.62{col 65}{space 3}0.105{col 73}{space 4}-.1407015{col 86}{space 3} .0133134
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0937452{col 45}{space 2} .1225484{col 56}{space 1}    0.76{col 65}{space 3}0.444{col 73}{space 4}-.1465645{col 86}{space 3} .3340549
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0610514{col 45}{space 2} .0773994{col 56}{space 1}    0.79{col 65}{space 3}0.430{col 73}{space 4} -.090724{col 86}{space 3} .2128269
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0234719{col 45}{space 2} .0639473{col 56}{space 1}    0.37{col 65}{space 3}0.714{col 73}{space 4}-.1019248{col 86}{space 3} .1488686
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0912524{col 45}{space 2} .0629768{col 56}{space 1}    1.45{col 65}{space 3}0.147{col 73}{space 4}-.0322411{col 86}{space 3}  .214746
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0250588{col 45}{space 2} .0677477{col 56}{space 1}   -0.37{col 65}{space 3}0.712{col 73}{space 4}-.1579078{col 86}{space 3} .1077901
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0333557{col 45}{space 2} .0870574{col 56}{space 1}   -0.38{col 65}{space 3}0.702{col 73}{space 4}-.2040697{col 86}{space 3} .1373584
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} .1467836{col 45}{space 2} .1152939{col 56}{space 1}    1.27{col 65}{space 3}0.203{col 73}{space 4}-.0793005{col 86}{space 3} .3728677
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}-.0909299{col 45}{space 2} .1804147{col 56}{space 1}   -0.50{col 65}{space 3}0.614{col 73}{space 4}-.4447118{col 86}{space 3}  .262852
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}  .602171{col 45}{space 2} .1127131{col 56}{space 1}    5.34{col 65}{space 3}0.000{col 73}{space 4} .3811477{col 86}{space 3} .8231944
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0570236{col 45}{space 2} .2724336{col 56}{space 1}    0.21{col 65}{space 3}0.834{col 73}{space 4}-.4772018{col 86}{space 3} .5912489
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0077882{col 45}{space 2} .0058207{col 56}{space 1}    1.34{col 65}{space 3}0.181{col 73}{space 4}-.0036258{col 86}{space 3} .0192023
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000265{col 45}{space 2}  .000054{col 56}{space 1}    0.49{col 65}{space 3}0.624{col 73}{space 4}-.0000794{col 86}{space 3} .0001324
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} .0276719{col 45}{space 2} .0722838{col 56}{space 1}    0.38{col 65}{space 3}0.702{col 73}{space 4}-.1140722{col 86}{space 3} .1694159
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} .0277336{col 45}{space 2} .0829494{col 56}{space 1}    0.33{col 65}{space 3}0.738{col 73}{space 4}-.1349251{col 86}{space 3} .1903922
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} .0077288{col 45}{space 2}  .090411{col 56}{space 1}    0.09{col 65}{space 3}0.932{col 73}{space 4}-.1695616{col 86}{space 3} .1850191
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} .0531507{col 45}{space 2} .0878092{col 56}{space 1}    0.61{col 65}{space 3}0.545{col 73}{space 4}-.1190377{col 86}{space 3}  .225339
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0370052{col 45}{space 2} .0914283{col 56}{space 1}   -0.40{col 65}{space 3}0.686{col 73}{space 4}-.2162905{col 86}{space 3}   .14228
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2}-2.553814{col 45}{space 2} .1341099{col 56}{space 1}  -19.04{col 65}{space 3}0.000{col 73}{space 4}-2.816795{col 86}{space 3}-2.290833
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .027429{col 45}{space 2} .0737666{col 56}{space 1}    0.37{col 65}{space 3}0.710{col 73}{space 4}-.1172227{col 86}{space 3} .1720806
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} -.093676{col 45}{space 2} .0724188{col 56}{space 1}   -1.29{col 65}{space 3}0.196{col 73}{space 4}-.2356848{col 86}{space 3} .0483328
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0751089{col 45}{space 2} .0844708{col 56}{space 1}   -0.89{col 65}{space 3}0.374{col 73}{space 4}-.2407509{col 86}{space 3} .0905331
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0942394{col 45}{space 2} .0760359{col 56}{space 1}   -1.24{col 65}{space 3}0.215{col 73}{space 4} -.243341{col 86}{space 3} .0548623
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1353231{col 45}{space 2}  .093223{col 56}{space 1}   -1.45{col 65}{space 3}0.147{col 73}{space 4}-.3181275{col 86}{space 3} .0474813
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} .1421195{col 45}{space 2} .1138771{col 56}{space 1}    1.25{col 65}{space 3}0.212{col 73}{space 4}-.0811863{col 86}{space 3} .3654253
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0095541{col 45}{space 2} .1017308{col 56}{space 1}   -0.09{col 65}{space 3}0.925{col 73}{space 4}-.2090418{col 86}{space 3} .1899337
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0953281{col 45}{space 2} .0941356{col 56}{space 1}    1.01{col 65}{space 3}0.311{col 73}{space 4}-.0892659{col 86}{space 3} .2799221
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0966644{col 45}{space 2} .1047751{col 56}{space 1}    0.92{col 65}{space 3}0.356{col 73}{space 4}-.1087929{col 86}{space 3} .3021218
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0061724{col 45}{space 2} .1065461{col 56}{space 1}   -0.06{col 65}{space 3}0.954{col 73}{space 4}-.2151028{col 86}{space 3} .2027579
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2} .0078104{col 45}{space 2} .0847582{col 56}{space 1}    0.09{col 65}{space 3}0.927{col 73}{space 4}-.1583951{col 86}{space 3} .1740159
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0086873{col 45}{space 2} .0940474{col 56}{space 1}   -0.09{col 65}{space 3}0.926{col 73}{space 4}-.1931084{col 86}{space 3} .1757338
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}-.0286177{col 45}{space 2}  .099057{col 56}{space 1}   -0.29{col 65}{space 3}0.773{col 73}{space 4}-.2228622{col 86}{space 3} .1656269
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0044396{col 45}{space 2} .0800586{col 56}{space 1}   -0.06{col 65}{space 3}0.956{col 73}{space 4}-.1614294{col 86}{space 3} .1525502
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.1025618{col 45}{space 2} .0808644{col 56}{space 1}   -1.27{col 65}{space 3}0.205{col 73}{space 4}-.2611319{col 86}{space 3} .0560082
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0173001{col 45}{space 2} .0898435{col 56}{space 1}   -0.19{col 65}{space 3}0.847{col 73}{space 4}-.1934775{col 86}{space 3} .1588773
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.2510739{col 45}{space 2} .0971243{col 56}{space 1}   -2.59{col 65}{space 3}0.010{col 73}{space 4}-.4415287{col 86}{space 3}-.0606192
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.2346363{col 45}{space 2} .0967051{col 56}{space 1}   -2.43{col 65}{space 3}0.015{col 73}{space 4}-.4242689{col 86}{space 3}-.0450037
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1606886{col 45}{space 2} .0873824{col 56}{space 1}    1.84{col 65}{space 3}0.066{col 73}{space 4}-.0106628{col 86}{space 3}   .33204
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0365213{col 45}{space 2} .1161293{col 56}{space 1}   -0.31{col 65}{space 3}0.753{col 73}{space 4}-.2642436{col 86}{space 3}  .191201
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} .1353471{col 45}{space 2} .0999293{col 56}{space 1}    1.35{col 65}{space 3}0.176{col 73}{space 4} -.060608{col 86}{space 3} .3313022
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}  .070583{col 45}{space 2} .1381814{col 56}{space 1}    0.51{col 65}{space 3}0.610{col 73}{space 4}-.2003821{col 86}{space 3} .3415481
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1614988{col 45}{space 2} .1547437{col 56}{space 1}    1.04{col 65}{space 3}0.297{col 73}{space 4}-.1419438{col 86}{space 3} .4649415
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .3146516{col 45}{space 2} .1201321{col 56}{space 1}    2.62{col 65}{space 3}0.009{col 73}{space 4} .0790801{col 86}{space 3} .5502231
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} 3.104145{col 45}{space 2} .1732546{col 56}{space 1}   17.92{col 65}{space 3}0.000{col 73}{space 4} 2.764403{col 86}{space 3} 3.443886
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                               Number of obs     = {res}     2,445
                                                {txt}{help j_robustsingular:F(43, 2400) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.1404
                                                {txt}Root MSE          =    {res} .79361

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                   vote_loyalty{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1253854{col 45}{space 2} .0432816{col 56}{space 1}    2.90{col 65}{space 3}0.004{col 73}{space 4} .0405121{col 86}{space 3} .2102586
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0498992{col 45}{space 2} .0352964{col 56}{space 1}    1.41{col 65}{space 3}0.158{col 73}{space 4}-.0193154{col 86}{space 3} .1191137
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .1351738{col 45}{space 2} .1090908{col 56}{space 1}    1.24{col 65}{space 3}0.215{col 73}{space 4}-.0787482{col 86}{space 3} .3490958
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .1199886{col 45}{space 2} .0700885{col 56}{space 1}    1.71{col 65}{space 3}0.087{col 73}{space 4}-.0174517{col 86}{space 3}  .257429
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0655496{col 45}{space 2} .0577811{col 56}{space 1}    1.13{col 65}{space 3}0.257{col 73}{space 4}-.0477565{col 86}{space 3} .1788557
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0580927{col 45}{space 2}  .056804{col 56}{space 1}    1.02{col 65}{space 3}0.307{col 73}{space 4}-.0532973{col 86}{space 3} .1694826
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0033683{col 45}{space 2} .0590938{col 56}{space 1}   -0.06{col 65}{space 3}0.955{col 73}{space 4}-.1192484{col 86}{space 3} .1125119
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0125801{col 45}{space 2} .0798656{col 56}{space 1}   -0.16{col 65}{space 3}0.875{col 73}{space 4}-.1691927{col 86}{space 3} .1440325
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} .0160388{col 45}{space 2} .1059681{col 56}{space 1}    0.15{col 65}{space 3}0.880{col 73}{space 4}-.1917596{col 86}{space 3} .2238372
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} -.132591{col 45}{space 2} .1298368{col 56}{space 1}   -1.02{col 65}{space 3}0.307{col 73}{space 4}-.3871947{col 86}{space 3} .1220128
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.6320986{col 45}{space 2}  .315128{col 56}{space 1}   -2.01{col 65}{space 3}0.045{col 73}{space 4} -1.25005{col 86}{space 3}-.0141474
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}   .09923{col 45}{space 2}  .362486{col 56}{space 1}    0.27{col 65}{space 3}0.784{col 73}{space 4} -.611588{col 86}{space 3} .8100479
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0029693{col 45}{space 2} .0053553{col 56}{space 1}   -0.55{col 65}{space 3}0.579{col 73}{space 4}-.0134708{col 86}{space 3} .0075322
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0001363{col 45}{space 2} .0000515{col 56}{space 1}    2.65{col 65}{space 3}0.008{col 73}{space 4} .0000354{col 86}{space 3} .0002372
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} .0137607{col 45}{space 2} .0832482{col 56}{space 1}    0.17{col 65}{space 3}0.869{col 73}{space 4}-.1494851{col 86}{space 3} .1770065
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0456737{col 45}{space 2} .0889037{col 56}{space 1}   -0.51{col 65}{space 3}0.607{col 73}{space 4}-.2200097{col 86}{space 3} .1286623
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1365769{col 45}{space 2} .0954809{col 56}{space 1}   -1.43{col 65}{space 3}0.153{col 73}{space 4}-.3238105{col 86}{space 3} .0506567
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1986378{col 45}{space 2} .0937395{col 56}{space 1}   -2.12{col 65}{space 3}0.034{col 73}{space 4}-.3824565{col 86}{space 3}-.0148192
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.2544921{col 45}{space 2} .0962283{col 56}{space 1}   -2.64{col 65}{space 3}0.008{col 73}{space 4}-.4431911{col 86}{space 3} -.065793
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2} -1.38941{col 45}{space 2} .1356837{col 56}{space 1}  -10.24{col 65}{space 3}0.000{col 73}{space 4} -1.65548{col 86}{space 3}-1.123341
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0331484{col 45}{space 2} .0723608{col 56}{space 1}    0.46{col 65}{space 3}0.647{col 73}{space 4}-.1087478{col 86}{space 3} .1750445
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}  -.07821{col 45}{space 2} .0697651{col 56}{space 1}   -1.12{col 65}{space 3}0.262{col 73}{space 4}-.2150162{col 86}{space 3} .0585962
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} -.094625{col 45}{space 2} .0806426{col 56}{space 1}   -1.17{col 65}{space 3}0.241{col 73}{space 4}-.2527613{col 86}{space 3} .0635113
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0642667{col 45}{space 2} .0717316{col 56}{space 1}   -0.90{col 65}{space 3}0.370{col 73}{space 4} -.204929{col 86}{space 3} .0763956
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0624925{col 45}{space 2} .0891339{col 56}{space 1}   -0.70{col 65}{space 3}0.483{col 73}{space 4}  -.23728{col 86}{space 3} .1122949
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} .0627153{col 45}{space 2} .1047392{col 56}{space 1}    0.60{col 65}{space 3}0.549{col 73}{space 4}-.1426733{col 86}{space 3} .2681039
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.1100582{col 45}{space 2} .0985329{col 56}{space 1}   -1.12{col 65}{space 3}0.264{col 73}{space 4}-.3032766{col 86}{space 3} .0831602
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.0695981{col 45}{space 2} .0862335{col 56}{space 1}   -0.81{col 65}{space 3}0.420{col 73}{space 4}-.2386979{col 86}{space 3} .0995018
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} -.046332{col 45}{space 2} .1015685{col 56}{space 1}   -0.46{col 65}{space 3}0.648{col 73}{space 4} -.245503{col 86}{space 3}  .152839
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.1634409{col 45}{space 2}  .090335{col 56}{space 1}   -1.81{col 65}{space 3}0.071{col 73}{space 4}-.3405837{col 86}{space 3} .0137018
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0592833{col 45}{space 2} .0839935{col 56}{space 1}   -0.71{col 65}{space 3}0.480{col 73}{space 4}-.2239906{col 86}{space 3}  .105424
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.1521425{col 45}{space 2} .0863404{col 56}{space 1}   -1.76{col 65}{space 3}0.078{col 73}{space 4} -.321452{col 86}{space 3}  .017167
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}-.1219659{col 45}{space 2} .0861243{col 56}{space 1}   -1.42{col 65}{space 3}0.157{col 73}{space 4}-.2908515{col 86}{space 3} .0469198
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.1120693{col 45}{space 2} .0772224{col 56}{space 1}   -1.45{col 65}{space 3}0.147{col 73}{space 4}-.2634987{col 86}{space 3} .0393601
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.2283466{col 45}{space 2} .0650566{col 56}{space 1}   -3.51{col 65}{space 3}0.000{col 73}{space 4}-.3559195{col 86}{space 3}-.1007737
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.2489714{col 45}{space 2} .0796625{col 56}{space 1}   -3.13{col 65}{space 3}0.002{col 73}{space 4}-.4051858{col 86}{space 3}-.0927569
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.135867{col 45}{space 2} .0829575{col 56}{space 1}   -1.64{col 65}{space 3}0.102{col 73}{space 4}-.2985428{col 86}{space 3} .0268087
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.2517397{col 45}{space 2} .0735735{col 56}{space 1}   -3.42{col 65}{space 3}0.001{col 73}{space 4}-.3960138{col 86}{space 3}-.1074656
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0860024{col 45}{space 2} .0931036{col 56}{space 1}   -0.92{col 65}{space 3}0.356{col 73}{space 4}-.2685741{col 86}{space 3} .0965694
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0291129{col 45}{space 2} .1133887{col 56}{space 1}   -0.26{col 65}{space 3}0.797{col 73}{space 4}-.2514628{col 86}{space 3} .1932371
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} .3042897{col 45}{space 2} .0948499{col 56}{space 1}    3.21{col 65}{space 3}0.001{col 73}{space 4} .1182935{col 86}{space 3}  .490286
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} .0147632{col 45}{space 2} .1091712{col 56}{space 1}    0.14{col 65}{space 3}0.892{col 73}{space 4}-.1993163{col 86}{space 3} .2288428
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1990249{col 45}{space 2} .1479305{col 56}{space 1}    1.35{col 65}{space 3}0.179{col 73}{space 4}-.0910599{col 86}{space 3} .4891096
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0078408{col 45}{space 2}  .162815{col 56}{space 1}    0.05{col 65}{space 3}0.962{col 73}{space 4}-.3114317{col 86}{space 3} .3271134
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}  1.99636{col 45}{space 2} .1604001{col 56}{space 1}   12.45{col 65}{space 3}0.000{col 73}{space 4} 1.681823{col 86}{space 3} 2.310897
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * Make table
. esttab wp_had_doubts wp_voted_conviction wp_vote_decision_long_ago wp_vote_loyalty using 03_tables/tablee2.tex, tex se replace  keep (pp_dummy) coeflabels (pp_dummy "PP voter") star(* 0.10 ** 0.05 *** 0.01) mtitles("Doubted vote choice" "Voted with conviction" "Decided vote long ago" "Loyal voter") addnotes("Standard errors are robust" "All models include region fixed effects" "All models include controls for income, education, age, age squared, size" " of respondent's municipality, and a dummy for respondents identifying as female")
{res}{txt}(output written to {browse  `"03_tables/tablee2.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tablef1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Run analyses
. regr cabine_use cs_dummy if pp_dummy == 0, r

{txt}Linear regression                               Number of obs     = {res}     1,586
                                                {txt}F(1, 1584)        =  {res}     0.90
                                                {txt}Prob > F          = {res}    0.3432
                                                {txt}R-squared         = {res}    0.0006
                                                {txt}Root MSE          =    {res}  .4947

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}cs_dummy {c |}{col 14}{res}{space 2} .0406795{col 26}{space 2} .0429047{col 37}{space 1}    0.95{col 46}{space 3}0.343{col 54}{space 4}-.0434765{col 67}{space 3} .1248354
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4224078{col 26}{space 2} .0130383{col 37}{space 1}   32.40{col 46}{space 3}0.000{col 54}{space 4} .3968336{col 67}{space 3}  .447982
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store other_cs_nocontrols
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. 
. regr cabine_use cs_dummy female i.income age age_sq i.education i.TAMUNI i.CCAA if pp_dummy == 0, r

{txt}Linear regression                               Number of obs     = {res}     1,175
                                                {txt}F(43, 1131)       =  {res}    15.58
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2317
                                                {txt}Root MSE          =    {res} .44519

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}cs_dummy {c |}{col 33}{res}{space 2} .0316128{col 45}{space 2} .0436451{col 56}{space 1}    0.72{col 65}{space 3}0.469{col 73}{space 4}-.0540216{col 86}{space 3} .1172473
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0028845{col 45}{space 2} .0283148{col 56}{space 1}    0.10{col 65}{space 3}0.919{col 73}{space 4}-.0526709{col 86}{space 3} .0584399
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0508062{col 45}{space 2} .1026511{col 56}{space 1}   -0.49{col 65}{space 3}0.621{col 73}{space 4}-.2522142{col 86}{space 3} .1506017
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0002955{col 45}{space 2} .0623802{col 56}{space 1}    0.00{col 65}{space 3}0.996{col 73}{space 4}-.1220984{col 86}{space 3} .1226893
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} -.032685{col 45}{space 2} .0495625{col 56}{space 1}   -0.66{col 65}{space 3}0.510{col 73}{space 4}-.1299297{col 86}{space 3} .0645597
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} -.038019{col 45}{space 2} .0465204{col 56}{space 1}   -0.82{col 65}{space 3}0.414{col 73}{space 4} -.129295{col 86}{space 3}  .053257
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0189407{col 45}{space 2} .0495739{col 56}{space 1}   -0.38{col 65}{space 3}0.702{col 73}{space 4}-.1162078{col 86}{space 3} .0783263
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0237487{col 45}{space 2} .0587652{col 56}{space 1}    0.40{col 65}{space 3}0.686{col 73}{space 4}-.0915523{col 86}{space 3} .1390497
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0478802{col 45}{space 2}   .08504{col 56}{space 1}   -0.56{col 65}{space 3}0.574{col 73}{space 4} -.214734{col 86}{space 3} .1189737
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}  .206037{col 45}{space 2} .1149755{col 56}{space 1}    1.79{col 65}{space 3}0.073{col 73}{space 4}-.0195523{col 86}{space 3} .4316264
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.420313{col 45}{space 2} .1730909{col 56}{space 1}   -2.43{col 65}{space 3}0.015{col 73}{space 4}-.7599283{col 86}{space 3}-.0806977
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .3273747{col 45}{space 2} .1573354{col 56}{space 1}    2.08{col 65}{space 3}0.038{col 73}{space 4} .0186726{col 86}{space 3} .6360769
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0015677{col 45}{space 2} .0049341{col 56}{space 1}   -0.32{col 65}{space 3}0.751{col 73}{space 4}-.0112487{col 86}{space 3} .0081134
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000107{col 45}{space 2} .0000517{col 56}{space 1}   -0.21{col 65}{space 3}0.835{col 73}{space 4}-.0001121{col 86}{space 3} .0000906
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0982556{col 45}{space 2} .1146598{col 56}{space 1}   -0.86{col 65}{space 3}0.392{col 73}{space 4}-.3232255{col 86}{space 3} .1267143
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1865224{col 45}{space 2} .1165832{col 56}{space 1}   -1.60{col 65}{space 3}0.110{col 73}{space 4} -.415266{col 86}{space 3} .0422213
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2201027{col 45}{space 2} .1181693{col 56}{space 1}   -1.86{col 65}{space 3}0.063{col 73}{space 4}-.4519584{col 86}{space 3} .0117531
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} -.150839{col 45}{space 2} .1174706{col 56}{space 1}   -1.28{col 65}{space 3}0.199{col 73}{space 4}-.3813238{col 86}{space 3} .0796457
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1495074{col 45}{space 2} .1188233{col 56}{space 1}   -1.26{col 65}{space 3}0.209{col 73}{space 4}-.3826463{col 86}{space 3} .0836315
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0057473{col 45}{space 2} .0674969{col 56}{space 1}   -0.09{col 65}{space 3}0.932{col 73}{space 4}-.1381804{col 86}{space 3} .1266858
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} -.113105{col 45}{space 2}  .064769{col 56}{space 1}   -1.75{col 65}{space 3}0.081{col 73}{space 4}-.2401859{col 86}{space 3} .0139758
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1568675{col 45}{space 2} .0731393{col 56}{space 1}   -2.14{col 65}{space 3}0.032{col 73}{space 4}-.3003715{col 86}{space 3}-.0133635
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.1914248{col 45}{space 2}  .066947{col 56}{space 1}   -2.86{col 65}{space 3}0.004{col 73}{space 4}-.3227791{col 86}{space 3}-.0600706
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.365517{col 45}{space 2} .0748842{col 56}{space 1}   -4.88{col 65}{space 3}0.000{col 73}{space 4}-.5124446{col 86}{space 3}-.2185894
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2104219{col 45}{space 2} .0706298{col 56}{space 1}   -2.98{col 65}{space 3}0.003{col 73}{space 4}-.3490021{col 86}{space 3}-.0718416
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0174719{col 45}{space 2} .0739488{col 56}{space 1}   -0.24{col 65}{space 3}0.813{col 73}{space 4}-.1625641{col 86}{space 3} .1276202
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2199781{col 45}{space 2} .0760594{col 56}{space 1}   -2.89{col 65}{space 3}0.004{col 73}{space 4}-.3692115{col 86}{space 3}-.0707447
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1276654{col 45}{space 2} .0836798{col 56}{space 1}   -1.53{col 65}{space 3}0.127{col 73}{space 4}-.2918505{col 86}{space 3} .0365197
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3744451{col 45}{space 2} .0575534{col 56}{space 1}    6.51{col 65}{space 3}0.000{col 73}{space 4} .2615216{col 86}{space 3} .4873686
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0122935{col 45}{space 2}  .075913{col 56}{space 1}   -0.16{col 65}{space 3}0.871{col 73}{space 4}-.1612397{col 86}{space 3} .1366526
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0047909{col 45}{space 2} .0836061{col 56}{space 1}    0.06{col 65}{space 3}0.954{col 73}{space 4}-.1592496{col 86}{space 3} .1688313
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}  .051952{col 45}{space 2} .0796315{col 56}{space 1}    0.65{col 65}{space 3}0.514{col 73}{space 4}  -.10429{col 86}{space 3} .2081941
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4249565{col 45}{space 2} .0512489{col 56}{space 1}   -8.29{col 65}{space 3}0.000{col 73}{space 4}-.5255102{col 86}{space 3}-.3244028
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0530939{col 45}{space 2} .0597775{col 56}{space 1}   -0.89{col 65}{space 3}0.375{col 73}{space 4}-.1703811{col 86}{space 3} .0641934
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1598385{col 45}{space 2} .0705721{col 56}{space 1}    2.26{col 65}{space 3}0.024{col 73}{space 4} .0213715{col 86}{space 3} .2983054
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} .0433507{col 45}{space 2} .0752502{col 56}{space 1}    0.58{col 65}{space 3}0.565{col 73}{space 4} -.104295{col 86}{space 3} .1909964
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3691898{col 45}{space 2} .0517627{col 56}{space 1}   -7.13{col 65}{space 3}0.000{col 73}{space 4}-.4707515{col 86}{space 3}-.2676281
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1326726{col 45}{space 2} .0745816{col 56}{space 1}    1.78{col 65}{space 3}0.076{col 73}{space 4}-.0136613{col 86}{space 3} .2790066
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1590079{col 45}{space 2} .0939088{col 56}{space 1}   -1.69{col 65}{space 3}0.091{col 73}{space 4} -.343263{col 86}{space 3} .0252471
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1113218{col 45}{space 2} .0917135{col 56}{space 1}   -1.21{col 65}{space 3}0.225{col 73}{space 4}-.2912695{col 86}{space 3} .0686259
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0623504{col 45}{space 2} .1280294{col 56}{space 1}   -0.49{col 65}{space 3}0.626{col 73}{space 4}-.3135522{col 86}{space 3} .1888514
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2494302{col 45}{space 2} .1083203{col 56}{space 1}    2.30{col 65}{space 3}0.021{col 73}{space 4} .0368989{col 86}{space 3} .4619615
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1237449{col 45}{space 2} .1441827{col 56}{space 1}    0.86{col 65}{space 3}0.391{col 73}{space 4}-.1591509{col 86}{space 3} .4066406
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9505243{col 45}{space 2} .1557521{col 56}{space 1}    6.10{col 65}{space 3}0.000{col 73}{space 4} .6449289{col 86}{space 3}  1.25612
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store other_cs_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. 
. regr cabine_use vox_dummy if pp_dummy == 0, r

{txt}Linear regression                               Number of obs     = {res}     1,586
                                                {txt}F(1, 1584)        =  {res}    10.75
                                                {txt}Prob > F          = {res}    0.0011
                                                {txt}R-squared         = {res}    0.0069
                                                {txt}Root MSE          =    {res} .49313

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}vox_dummy {c |}{col 14}{res}{space 2} .1112473{col 26}{space 2} .0339247{col 37}{space 1}    3.28{col 46}{space 3}0.001{col 54}{space 4} .0447053{col 67}{space 3} .1777894
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4081325{col 26}{space 2} .0134955{col 37}{space 1}   30.24{col 46}{space 3}0.000{col 54}{space 4} .3816617{col 67}{space 3} .4346034
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store other_vox_nocontrols
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. 
. regr cabine_use vox_dummy female i.income age age_sq i.education i.TAMUNI i.CCAA if pp_dummy == 0, r

{txt}Linear regression                               Number of obs     = {res}     1,175
                                                {txt}F(43, 1131)       =  {res}    15.21
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2318
                                                {txt}Root MSE          =    {res} .44517

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}vox_dummy {c |}{col 33}{res}{space 2} .0295126{col 45}{space 2} .0384782{col 56}{space 1}    0.77{col 65}{space 3}0.443{col 73}{space 4}-.0459841{col 86}{space 3} .1050093
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0059264{col 45}{space 2} .0283455{col 56}{space 1}    0.21{col 65}{space 3}0.834{col 73}{space 4}-.0496893{col 86}{space 3}  .061542
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0508809{col 45}{space 2} .1023432{col 56}{space 1}   -0.50{col 65}{space 3}0.619{col 73}{space 4}-.2516847{col 86}{space 3} .1499229
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0003865{col 45}{space 2} .0623877{col 56}{space 1}    0.01{col 65}{space 3}0.995{col 73}{space 4}-.1220222{col 86}{space 3} .1227952
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0345941{col 45}{space 2} .0496982{col 56}{space 1}   -0.70{col 65}{space 3}0.487{col 73}{space 4}-.1321051{col 86}{space 3} .0629169
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0398145{col 45}{space 2} .0464519{col 56}{space 1}   -0.86{col 65}{space 3}0.392{col 73}{space 4}-.1309561{col 86}{space 3} .0513271
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} -.019718{col 45}{space 2}  .049615{col 56}{space 1}   -0.40{col 65}{space 3}0.691{col 73}{space 4}-.1170658{col 86}{space 3} .0776297
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0217556{col 45}{space 2} .0588314{col 56}{space 1}    0.37{col 65}{space 3}0.712{col 73}{space 4}-.0936753{col 86}{space 3} .1371865
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0475968{col 45}{space 2} .0849538{col 56}{space 1}   -0.56{col 65}{space 3}0.575{col 73}{space 4}-.2142815{col 86}{space 3} .1190879
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .2098285{col 45}{space 2} .1152929{col 56}{space 1}    1.82{col 65}{space 3}0.069{col 73}{space 4}-.0163835{col 86}{space 3} .4360406
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4409309{col 45}{space 2} .1828601{col 56}{space 1}   -2.41{col 65}{space 3}0.016{col 73}{space 4}-.7997141{col 86}{space 3}-.0821476
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .3142008{col 45}{space 2}  .160503{col 56}{space 1}    1.96{col 65}{space 3}0.051{col 73}{space 4}-.0007163{col 86}{space 3}  .629118
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0014492{col 45}{space 2} .0049458{col 56}{space 1}   -0.29{col 65}{space 3}0.770{col 73}{space 4}-.0111531{col 86}{space 3} .0082547
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000118{col 45}{space 2} .0000517{col 56}{space 1}   -0.23{col 65}{space 3}0.819{col 73}{space 4}-.0001134{col 86}{space 3} .0000897
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0983265{col 45}{space 2} .1145002{col 56}{space 1}   -0.86{col 65}{space 3}0.391{col 73}{space 4}-.3229831{col 86}{space 3} .1263302
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1921888{col 45}{space 2} .1163673{col 56}{space 1}   -1.65{col 65}{space 3}0.099{col 73}{space 4}-.4205089{col 86}{space 3} .0361312
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2224657{col 45}{space 2} .1179569{col 56}{space 1}   -1.89{col 65}{space 3}0.060{col 73}{space 4}-.4539047{col 86}{space 3} .0089734
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1533764{col 45}{space 2} .1172502{col 56}{space 1}   -1.31{col 65}{space 3}0.191{col 73}{space 4}-.3834287{col 86}{space 3}  .076676
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1483685{col 45}{space 2} .1186615{col 56}{space 1}   -1.25{col 65}{space 3}0.211{col 73}{space 4}  -.38119{col 86}{space 3} .0844529
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0049494{col 45}{space 2} .0675817{col 56}{space 1}   -0.07{col 65}{space 3}0.942{col 73}{space 4} -.137549{col 86}{space 3} .1276502
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1110678{col 45}{space 2}  .064933{col 56}{space 1}   -1.71{col 65}{space 3}0.087{col 73}{space 4}-.2384705{col 86}{space 3} .0163349
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1584107{col 45}{space 2} .0732497{col 56}{space 1}   -2.16{col 65}{space 3}0.031{col 73}{space 4}-.3021312{col 86}{space 3}-.0146902
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} -.190426{col 45}{space 2}  .067002{col 56}{space 1}   -2.84{col 65}{space 3}0.005{col 73}{space 4}-.3218882{col 86}{space 3}-.0589638
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3620563{col 45}{space 2} .0748385{col 56}{space 1}   -4.84{col 65}{space 3}0.000{col 73}{space 4}-.5088942{col 86}{space 3}-.2152184
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2110209{col 45}{space 2} .0707362{col 56}{space 1}   -2.98{col 65}{space 3}0.003{col 73}{space 4}-.3498098{col 86}{space 3}-.0722321
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0186781{col 45}{space 2}  .074054{col 56}{space 1}   -0.25{col 65}{space 3}0.801{col 73}{space 4}-.1639767{col 86}{space 3} .1266205
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2227363{col 45}{space 2} .0756853{col 56}{space 1}   -2.94{col 65}{space 3}0.003{col 73}{space 4}-.3712357{col 86}{space 3}-.0742369
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1326303{col 45}{space 2} .0834163{col 56}{space 1}   -1.59{col 65}{space 3}0.112{col 73}{space 4}-.2962985{col 86}{space 3} .0310379
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3748759{col 45}{space 2} .0576791{col 56}{space 1}    6.50{col 65}{space 3}0.000{col 73}{space 4} .2617059{col 86}{space 3} .4880459
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0114904{col 45}{space 2}  .075989{col 56}{space 1}   -0.15{col 65}{space 3}0.880{col 73}{space 4}-.1605856{col 86}{space 3} .1376048
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0005793{col 45}{space 2} .0838799{col 56}{space 1}   -0.01{col 65}{space 3}0.994{col 73}{space 4}-.1651571{col 86}{space 3} .1639984
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0508262{col 45}{space 2} .0791094{col 56}{space 1}    0.64{col 65}{space 3}0.521{col 73}{space 4}-.1043914{col 86}{space 3} .2060439
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} -.422809{col 45}{space 2} .0513948{col 56}{space 1}   -8.23{col 65}{space 3}0.000{col 73}{space 4}-.5236489{col 86}{space 3}-.3219691
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} -.055371{col 45}{space 2} .0596707{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.1724488{col 86}{space 3} .0617067
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1607293{col 45}{space 2} .0710272{col 56}{space 1}    2.26{col 65}{space 3}0.024{col 73}{space 4} .0213695{col 86}{space 3} .3000892
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} .0410739{col 45}{space 2} .0752631{col 56}{space 1}    0.55{col 65}{space 3}0.585{col 73}{space 4} -.106597{col 86}{space 3} .1887448
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3693579{col 45}{space 2} .0518717{col 56}{space 1}   -7.12{col 65}{space 3}0.000{col 73}{space 4}-.4711334{col 86}{space 3}-.2675823
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1256437{col 45}{space 2} .0743131{col 56}{space 1}    1.69{col 65}{space 3}0.091{col 73}{space 4}-.0201633{col 86}{space 3} .2714507
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1592468{col 45}{space 2} .0937156{col 56}{space 1}   -1.70{col 65}{space 3}0.090{col 73}{space 4}-.3431228{col 86}{space 3} .0246291
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1114226{col 45}{space 2} .0914828{col 56}{space 1}   -1.22{col 65}{space 3}0.223{col 73}{space 4}-.2909177{col 86}{space 3} .0680725
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0665046{col 45}{space 2} .1287046{col 56}{space 1}   -0.52{col 65}{space 3}0.605{col 73}{space 4}-.3190312{col 86}{space 3} .1860219
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .231178{col 45}{space 2} .1099298{col 56}{space 1}    2.10{col 65}{space 3}0.036{col 73}{space 4} .0154886{col 86}{space 3} .4468673
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1198039{col 45}{space 2} .1426031{col 56}{space 1}    0.84{col 65}{space 3}0.401{col 73}{space 4}-.1599925{col 86}{space 3} .3996003
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9476276{col 45}{space 2} .1561012{col 56}{space 1}    6.07{col 65}{space 3}0.000{col 73}{space 4} .6413471{col 86}{space 3} 1.253908
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store other_vox_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. 
. * Make table (without full list of controls)
. esttab other_cs_nocontrols other_cs_controls other_vox_nocontrols other_vox_controls using 03_tables/tablef1.tex, tex se replace keep(cs_dummy vox_dummy) coeflabels (cs_dummy "Ciudadanos voter" vox_dummy "Vox voter") nomtitles star(* 0.10 ** 0.05 *** 0.01) s(Controls, label("Controls")) addnotes("Standard errors are robust" "The outcome variable is a dummy for whether each respondent used a private" "voting booth to cast their vote in the general election of November 2019" "Models 2 and 4 include controls for income, education, age, age squared, size of" "respondent's municipality, and a dummy for respondents identifying as female" "The analyses exclude respondents who voted for PP") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/tablef1.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tablef2.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Generate interactions
. gen cabine_use_cs = cabine_use * cs_dummy
{txt}(2,960 missing values generated)

{com}. gen cabine_use_vox = cabine_use * vox_dummy
{txt}(2,960 missing values generated)

{com}. 
. * Run analyses
. regr uncomfortable cabine_use cs_dummy cabine_use_cs if pp_dummy == 0, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,586
                                                {txt}F(3, 121)         =  {res}     0.60
                                                {txt}Prob > F          = {res}    0.6139
                                                {txt}R-squared         = {res}    0.0010
                                                {txt}Root MSE          =    {res} .29803

{txt}{ralign 79:(Std. err. adjusted for {res:122} clusters in {res:municipality})}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}uncomfortable{col 15}{c |} Coefficient{col 27}  std. err.{col 39}      t{col 47}   P>|t|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}cabine_use {c |}{col 15}{res}{space 2}-.0040055{col 27}{space 2} .0195347{col 38}{space 1}   -0.21{col 47}{space 3}0.838{col 55}{space 4}-.0426796{col 68}{space 3} .0346686
{txt}{space 5}cs_dummy {c |}{col 15}{res}{space 2} .0112952{col 27}{space 2} .0456465{col 38}{space 1}    0.25{col 47}{space 3}0.805{col 55}{space 4}-.0790742{col 68}{space 3} .1016646
{txt}cabine_use_cs {c |}{col 15}{res}{space 2}-.0505235{col 27}{space 2} .0581328{col 38}{space 1}   -0.87{col 47}{space 3}0.387{col 55}{space 4}-.1656127{col 68}{space 3} .0645657
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .1012048{col 27}{space 2} .0150045{col 38}{space 1}    6.74{col 47}{space 3}0.000{col 55}{space 4} .0714995{col 68}{space 3} .1309101
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_cs_nocontrols
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. 
. regr uncomfortable cabine_use cs_dummy cabine_use_cs female i.income age age_sq i.education i.TAMUNI i.CCAA if pp_dummy == 0, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,175
                                                {txt}{help j_robustsingular:F(43, 117) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0648
                                                {txt}Root MSE          =    {res} .27653

{txt}{ralign 97:(Std. err. adjusted for {res:118} clusters in {res:municipality})}
{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0109583{col 45}{space 2} .0214749{col 56}{space 1}   -0.51{col 65}{space 3}0.611{col 73}{space 4}-.0534881{col 86}{space 3} .0315716
{txt}{space 23}cs_dummy {c |}{col 33}{res}{space 2}  .019332{col 45}{space 2} .0558466{col 56}{space 1}    0.35{col 65}{space 3}0.730{col 73}{space 4}-.0912693{col 86}{space 3} .1299332
{txt}{space 18}cabine_use_cs {c |}{col 33}{res}{space 2}-.0819299{col 45}{space 2} .0665846{col 56}{space 1}   -1.23{col 65}{space 3}0.221{col 73}{space 4}-.2137972{col 86}{space 3} .0499374
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0321415{col 45}{space 2} .0188919{col 56}{space 1}    1.70{col 65}{space 3}0.092{col 73}{space 4}-.0052729{col 86}{space 3} .0695559
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0189942{col 45}{space 2} .0661553{col 56}{space 1}    0.29{col 65}{space 3}0.775{col 73}{space 4}-.1120229{col 86}{space 3} .1500113
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .046921{col 45}{space 2} .0416627{col 56}{space 1}    1.13{col 65}{space 3}0.262{col 73}{space 4}-.0355898{col 86}{space 3} .1294317
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0024535{col 45}{space 2} .0360349{col 56}{space 1}    0.07{col 65}{space 3}0.946{col 73}{space 4}-.0689119{col 86}{space 3} .0738188
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0070435{col 45}{space 2} .0284717{col 56}{space 1}    0.25{col 65}{space 3}0.805{col 73}{space 4}-.0493433{col 86}{space 3} .0634302
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0197295{col 45}{space 2} .0276463{col 56}{space 1}    0.71{col 65}{space 3}0.477{col 73}{space 4}-.0350227{col 86}{space 3} .0744816
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.030502{col 45}{space 2} .0377956{col 56}{space 1}   -0.81{col 65}{space 3}0.421{col 73}{space 4}-.1053541{col 86}{space 3} .0443502
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0389624{col 45}{space 2} .0398977{col 56}{space 1}   -0.98{col 65}{space 3}0.331{col 73}{space 4}-.1179777{col 86}{space 3} .0400529
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0934068{col 45}{space 2} .0959396{col 56}{space 1}    0.97{col 65}{space 3}0.332{col 73}{space 4}-.0965965{col 86}{space 3} .2834101
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0879119{col 45}{space 2} .0510298{col 56}{space 1}   -1.72{col 65}{space 3}0.088{col 73}{space 4}-.1889737{col 86}{space 3}   .01315
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0706422{col 45}{space 2}  .043749{col 56}{space 1}   -1.61{col 65}{space 3}0.109{col 73}{space 4}-.1572849{col 86}{space 3} .0160005
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0011295{col 45}{space 2} .0032877{col 56}{space 1}   -0.34{col 65}{space 3}0.732{col 73}{space 4}-.0076405{col 86}{space 3} .0053816
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000181{col 45}{space 2} .0000364{col 56}{space 1}    0.50{col 65}{space 3}0.619{col 73}{space 4}-.0000539{col 86}{space 3} .0000902
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1122454{col 45}{space 2} .1016779{col 56}{space 1}   -1.10{col 65}{space 3}0.272{col 73}{space 4}-.3136132{col 86}{space 3} .0891224
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0517292{col 45}{space 2} .1130343{col 56}{space 1}   -0.46{col 65}{space 3}0.648{col 73}{space 4}-.2755878{col 86}{space 3} .1721294
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0995348{col 45}{space 2} .1085185{col 56}{space 1}   -0.92{col 65}{space 3}0.361{col 73}{space 4}  -.31445{col 86}{space 3} .1153804
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0898664{col 45}{space 2}  .111426{col 56}{space 1}   -0.81{col 65}{space 3}0.422{col 73}{space 4}-.3105397{col 86}{space 3} .1308068
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0940855{col 45}{space 2} .1102921{col 56}{space 1}   -0.85{col 65}{space 3}0.395{col 73}{space 4}-.3125133{col 86}{space 3} .1243422
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .1056949{col 45}{space 2} .0352191{col 56}{space 1}    3.00{col 65}{space 3}0.003{col 73}{space 4} .0359454{col 86}{space 3} .1754444
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0620622{col 45}{space 2} .0264332{col 56}{space 1}    2.35{col 65}{space 3}0.021{col 73}{space 4} .0097127{col 86}{space 3} .1144118
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .052379{col 45}{space 2} .0401664{col 56}{space 1}    1.30{col 65}{space 3}0.195{col 73}{space 4}-.0271684{col 86}{space 3} .1319265
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0328742{col 45}{space 2} .0353404{col 56}{space 1}    0.93{col 65}{space 3}0.354{col 73}{space 4}-.0371157{col 86}{space 3} .1028641
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} .0048353{col 45}{space 2} .0362831{col 56}{space 1}    0.13{col 65}{space 3}0.894{col 73}{space 4}-.0670214{col 86}{space 3}  .076692
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.050799{col 45}{space 2} .0387284{col 56}{space 1}   -1.31{col 65}{space 3}0.192{col 73}{space 4}-.1274985{col 86}{space 3} .0259005
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0408821{col 45}{space 2} .0454402{col 56}{space 1}   -0.90{col 65}{space 3}0.370{col 73}{space 4} -.130874{col 86}{space 3} .0491097
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0145791{col 45}{space 2} .0446535{col 56}{space 1}    0.33{col 65}{space 3}0.745{col 73}{space 4}-.0738548{col 86}{space 3} .1030131
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0267574{col 45}{space 2} .0491006{col 56}{space 1}    0.54{col 65}{space 3}0.587{col 73}{space 4}-.0704839{col 86}{space 3} .1239987
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0589585{col 45}{space 2} .0461084{col 56}{space 1}   -1.28{col 65}{space 3}0.204{col 73}{space 4}-.1502739{col 86}{space 3} .0323569
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0270269{col 45}{space 2} .0489208{col 56}{space 1}   -0.55{col 65}{space 3}0.582{col 73}{space 4}-.1239119{col 86}{space 3} .0698582
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0693859{col 45}{space 2}  .078476{col 56}{space 1}    0.88{col 65}{space 3}0.378{col 73}{space 4}-.0860318{col 86}{space 3} .2248035
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0510389{col 45}{space 2} .0884237{col 56}{space 1}    0.58{col 65}{space 3}0.565{col 73}{space 4}-.1240795{col 86}{space 3} .2261573
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0060378{col 45}{space 2} .0492639{col 56}{space 1}   -0.12{col 65}{space 3}0.903{col 73}{space 4}-.1036025{col 86}{space 3} .0915268
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0596884{col 45}{space 2} .0532447{col 56}{space 1}   -1.12{col 65}{space 3}0.265{col 73}{space 4}-.1651368{col 86}{space 3} .0457599
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .0029224{col 45}{space 2} .0613462{col 56}{space 1}    0.05{col 65}{space 3}0.962{col 73}{space 4}-.1185704{col 86}{space 3} .1244153
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.1054866{col 45}{space 2} .0499624{col 56}{space 1}   -2.11{col 65}{space 3}0.037{col 73}{space 4}-.2044345{col 86}{space 3}-.0065386
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0721006{col 45}{space 2} .0580243{col 56}{space 1}    1.24{col 65}{space 3}0.217{col 73}{space 4}-.0428134{col 86}{space 3} .1870146
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0692468{col 45}{space 2} .0404954{col 56}{space 1}   -1.71{col 65}{space 3}0.090{col 73}{space 4}-.1494458{col 86}{space 3} .0109521
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0215804{col 45}{space 2} .0511505{col 56}{space 1}   -0.42{col 65}{space 3}0.674{col 73}{space 4}-.1228813{col 86}{space 3} .0797205
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.073995{col 45}{space 2} .0529582{col 56}{space 1}   -1.40{col 65}{space 3}0.165{col 73}{space 4}-.1788759{col 86}{space 3}  .030886
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.1084138{col 45}{space 2} .0468306{col 56}{space 1}   -2.32{col 65}{space 3}0.022{col 73}{space 4}-.2011592{col 86}{space 3}-.0156683
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0412362{col 45}{space 2} .0546744{col 56}{space 1}    0.75{col 65}{space 3}0.452{col 73}{space 4}-.0670436{col 86}{space 3}  .149516
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0006019{col 45}{space 2} .0486979{col 56}{space 1}   -0.01{col 65}{space 3}0.990{col 73}{space 4}-.0970457{col 86}{space 3} .0958418
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}  .131299{col 45}{space 2}  .120757{col 56}{space 1}    1.09{col 65}{space 3}0.279{col 73}{space 4} -.107854{col 86}{space 3}  .370452
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_cs_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. 
. regr uncomfortable cabine_use vox_dummy cabine_use_vox if pp_dummy == 0, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,586
                                                {txt}F(3, 121)         =  {res}     1.05
                                                {txt}Prob > F          = {res}    0.3745
                                                {txt}R-squared         = {res}    0.0018
                                                {txt}Root MSE          =    {res} .29792

{txt}{ralign 80:(Std. err. adjusted for {res:122} clusters in {res:municipality})}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1} uncomfortable{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}cabine_use {c |}{col 16}{res}{space 2}-.0194549{col 28}{space 2} .0207399{col 39}{space 1}   -0.94{col 48}{space 3}0.350{col 56}{space 4}-.0605149{col 69}{space 3} .0216052
{txt}{space 5}vox_dummy {c |}{col 16}{res}{space 2} -.015616{col 28}{space 2} .0274926{col 39}{space 1}   -0.57{col 48}{space 3}0.571{col 56}{space 4}-.0700449{col 69}{space 3} .0388128
{txt}cabine_use_vox {c |}{col 16}{res}{space 2} .0576108{col 28}{space 2} .0362683{col 39}{space 1}    1.59{col 48}{space 3}0.115{col 56}{space 4}-.0141918{col 69}{space 3} .1294135
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .1043257{col 28}{space 2} .0174006{col 39}{space 1}    6.00{col 48}{space 3}0.000{col 56}{space 4} .0698766{col 69}{space 3} .1387748
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_vox_nocontrols
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. 
. regr uncomfortable cabine_use vox_dummy cabine_use_vox female i.income age age_sq i.education i.TAMUNI i.CCAA if pp_dummy == 0, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,175
                                                {txt}{help j_robustsingular:F(43, 117) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0628
                                                {txt}Root MSE          =    {res} .27683

{txt}{ralign 97:(Std. err. adjusted for {res:118} clusters in {res:municipality})}
{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0219421{col 45}{space 2} .0219216{col 56}{space 1}   -1.00{col 65}{space 3}0.319{col 73}{space 4}-.0653568{col 86}{space 3} .0214725
{txt}{space 22}vox_dummy {c |}{col 33}{res}{space 2}-.0101061{col 45}{space 2}  .030666{col 56}{space 1}   -0.33{col 65}{space 3}0.742{col 73}{space 4}-.0708384{col 86}{space 3} .0506263
{txt}{space 17}cabine_use_vox {c |}{col 33}{res}{space 2}  .020594{col 45}{space 2} .0393184{col 56}{space 1}    0.52{col 65}{space 3}0.601{col 73}{space 4}-.0572741{col 86}{space 3} .0984621
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0305649{col 45}{space 2} .0185776{col 56}{space 1}    1.65{col 65}{space 3}0.103{col 73}{space 4}-.0062271{col 86}{space 3}  .067357
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0215732{col 45}{space 2} .0652708{col 56}{space 1}    0.33{col 65}{space 3}0.742{col 73}{space 4}-.1076923{col 86}{space 3} .1508386
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0480396{col 45}{space 2} .0419215{col 56}{space 1}    1.15{col 65}{space 3}0.254{col 73}{space 4}-.0349837{col 86}{space 3} .1310629
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}  .001894{col 45}{space 2} .0360533{col 56}{space 1}    0.05{col 65}{space 3}0.958{col 73}{space 4}-.0695077{col 86}{space 3} .0732957
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0079146{col 45}{space 2} .0286492{col 56}{space 1}    0.28{col 65}{space 3}0.783{col 73}{space 4}-.0488237{col 86}{space 3} .0646529
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}  .019158{col 45}{space 2} .0275637{col 56}{space 1}    0.70{col 65}{space 3}0.488{col 73}{space 4}-.0354306{col 86}{space 3} .0737465
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0307867{col 45}{space 2} .0381414{col 56}{space 1}   -0.81{col 65}{space 3}0.421{col 73}{space 4}-.1063236{col 86}{space 3} .0447503
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0353062{col 45}{space 2} .0441579{col 56}{space 1}   -0.80{col 65}{space 3}0.426{col 73}{space 4}-.1227586{col 86}{space 3} .0521461
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0866732{col 45}{space 2} .0961551{col 56}{space 1}    0.90{col 65}{space 3}0.369{col 73}{space 4}-.1037568{col 86}{space 3} .2771033
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0827838{col 45}{space 2} .0571119{col 56}{space 1}   -1.45{col 65}{space 3}0.150{col 73}{space 4} -.195891{col 86}{space 3} .0303234
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.066292{col 45}{space 2} .0444829{col 56}{space 1}   -1.49{col 65}{space 3}0.139{col 73}{space 4}-.1543882{col 86}{space 3} .0218041
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0009948{col 45}{space 2} .0033142{col 56}{space 1}   -0.30{col 65}{space 3}0.765{col 73}{space 4}-.0075585{col 86}{space 3} .0055688
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000167{col 45}{space 2} .0000366{col 56}{space 1}    0.46{col 65}{space 3}0.650{col 73}{space 4}-.0000559{col 86}{space 3} .0000893
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1187613{col 45}{space 2} .1013891{col 56}{space 1}   -1.17{col 65}{space 3}0.244{col 73}{space 4}-.3195571{col 86}{space 3} .0820346
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0577712{col 45}{space 2} .1130315{col 56}{space 1}   -0.51{col 65}{space 3}0.610{col 73}{space 4}-.2816242{col 86}{space 3} .1660818
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1049318{col 45}{space 2} .1084527{col 56}{space 1}   -0.97{col 65}{space 3}0.335{col 73}{space 4}-.3197168{col 86}{space 3} .1098532
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0965871{col 45}{space 2} .1116483{col 56}{space 1}   -0.87{col 65}{space 3}0.389{col 73}{space 4}-.3177008{col 86}{space 3} .1245265
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1015671{col 45}{space 2}  .110067{col 56}{space 1}   -0.92{col 65}{space 3}0.358{col 73}{space 4}-.3195491{col 86}{space 3} .1164149
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .1052011{col 45}{space 2} .0350578{col 56}{space 1}    3.00{col 65}{space 3}0.003{col 73}{space 4} .0357709{col 86}{space 3} .1746314
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0610777{col 45}{space 2} .0264741{col 56}{space 1}    2.31{col 65}{space 3}0.023{col 73}{space 4} .0086471{col 86}{space 3} .1135082
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0538772{col 45}{space 2} .0401063{col 56}{space 1}    1.34{col 65}{space 3}0.182{col 73}{space 4}-.0255511{col 86}{space 3} .1333055
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0340612{col 45}{space 2} .0351833{col 56}{space 1}    0.97{col 65}{space 3}0.335{col 73}{space 4}-.0356174{col 86}{space 3} .1037398
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} .0055592{col 45}{space 2} .0359875{col 56}{space 1}    0.15{col 65}{space 3}0.877{col 73}{space 4}-.0657121{col 86}{space 3} .0768306
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0520657{col 45}{space 2} .0389415{col 56}{space 1}   -1.34{col 65}{space 3}0.184{col 73}{space 4}-.1291873{col 86}{space 3}  .025056
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0414917{col 45}{space 2} .0452556{col 56}{space 1}   -0.92{col 65}{space 3}0.361{col 73}{space 4} -.131118{col 86}{space 3} .0481346
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0115386{col 45}{space 2} .0463902{col 56}{space 1}    0.25{col 65}{space 3}0.804{col 73}{space 4}-.0803348{col 86}{space 3} .1034121
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0271391{col 45}{space 2} .0482375{col 56}{space 1}    0.56{col 65}{space 3}0.575{col 73}{space 4}-.0683927{col 86}{space 3}  .122671
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0645757{col 45}{space 2} .0478781{col 56}{space 1}   -1.35{col 65}{space 3}0.180{col 73}{space 4}-.1593957{col 86}{space 3} .0302444
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0260489{col 45}{space 2} .0486385{col 56}{space 1}   -0.54{col 65}{space 3}0.593{col 73}{space 4}-.1223748{col 86}{space 3} .0702771
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0672492{col 45}{space 2} .0796543{col 56}{space 1}    0.84{col 65}{space 3}0.400{col 73}{space 4} -.090502{col 86}{space 3} .2250003
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0512261{col 45}{space 2} .0885941{col 56}{space 1}    0.58{col 65}{space 3}0.564{col 73}{space 4}-.1242299{col 86}{space 3} .2266821
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0054561{col 45}{space 2} .0494343{col 56}{space 1}   -0.11{col 65}{space 3}0.912{col 73}{space 4}-.1033581{col 86}{space 3}  .092446
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0590152{col 45}{space 2} .0535053{col 56}{space 1}   -1.10{col 65}{space 3}0.272{col 73}{space 4}-.1649797{col 86}{space 3} .0469492
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0014359{col 45}{space 2} .0615402{col 56}{space 1}   -0.02{col 65}{space 3}0.981{col 73}{space 4} -.123313{col 86}{space 3} .1204412
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.102022{col 45}{space 2} .0490824{col 56}{space 1}   -2.08{col 65}{space 3}0.040{col 73}{space 4}-.1992271{col 86}{space 3}-.0048169
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0720807{col 45}{space 2} .0585153{col 56}{space 1}    1.23{col 65}{space 3}0.220{col 73}{space 4}-.0438058{col 86}{space 3} .1879673
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} -.067926{col 45}{space 2} .0409147{col 56}{space 1}   -1.66{col 65}{space 3}0.100{col 73}{space 4}-.1489554{col 86}{space 3} .0131034
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2} -.019749{col 45}{space 2}  .051023{col 56}{space 1}   -0.39{col 65}{space 3}0.699{col 73}{space 4}-.1207974{col 86}{space 3} .0812994
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0714044{col 45}{space 2} .0524778{col 56}{space 1}   -1.36{col 65}{space 3}0.176{col 73}{space 4} -.175334{col 86}{space 3} .0325251
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} -.103385{col 45}{space 2} .0458394{col 56}{space 1}   -2.26{col 65}{space 3}0.026{col 73}{space 4}-.1941674{col 86}{space 3}-.0126025
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0406245{col 45}{space 2}  .057109{col 56}{space 1}    0.71{col 65}{space 3}0.478{col 73}{space 4} -.072477{col 86}{space 3}  .153726
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0004251{col 45}{space 2} .0489017{col 56}{space 1}   -0.01{col 65}{space 3}0.993{col 73}{space 4}-.0972724{col 86}{space 3} .0964223
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1383354{col 45}{space 2} .1203046{col 56}{space 1}    1.15{col 65}{space 3}0.253{col 73}{space 4}-.0999216{col 86}{space 3} .3765924
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store uncomf_vox_controls
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. 
. * Make table (without full list of controls)
. esttab uncomf_cs_nocontrols uncomf_cs_controls uncomf_vox_nocontrols uncomf_vox_controls using 03_tables/tablef2.tex, tex se replace keep(cabine_use cs_dummy vox_dummy cabine_use_cs cabine_use_vox) coeflabels (cabine_use "Used booth to vote" cs_dummy "Ciudadanos voter" vox_dummy "Vox voter" cabine_use_cs "Used booth x Cs voter" cabine_use_vox "Used booth x Vox voter") nomtitles star(* 0.10 ** 0.05 *** 0.01) s(Controls, label("Controls")) addnotes("Standard errors are clustered by municipality" "The outcome variable is a dummy for whether each respondent showed" "signs of discomfort during the survey interview" "Models 2 and 4 include controls for income, education, age, age squared, size of" "respondent's municipality, and a dummy for respondents identifying as female" "The analyses exclude respondents who voted for PP") scalars(e(N))
{res}{txt}(output written to {browse  `"03_tables/tablef2.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/tablef3.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Generate interaction
. gen prefdem_pp = democracy_pref * pp_dummy
{txt}(1,515 missing values generated)

{com}. 
. * Run analyses
. regr cabine_use democracy_pref, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,803
                                                {txt}F(1, 123)         =  {res}     6.18
                                                {txt}Prob > F          = {res}    0.0143
                                                {txt}R-squared         = {res}    0.0067
                                                {txt}Root MSE          =    {res} .49525

{txt}{ralign 80:(Std. err. adjusted for {res:124} clusters in {res:municipality})}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}    cabine_use{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
democracy_pref {c |}{col 16}{res}{space 2}-.1420741{col 28}{space 2} .0571493{col 39}{space 1}   -2.49{col 48}{space 3}0.014{col 56}{space 4}-.2551976{col 69}{space 3}-.0289506
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .5714286{col 28}{space 2} .0599532{col 39}{space 1}    9.53{col 48}{space 3}0.000{col 56}{space 4} .4527549{col 69}{space 3} .6901022
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store prefsystem_1
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. 
. regr cabine_use democracy_pref female i.income age age_sq i.education  i.TAMUNI i.CCAA, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,328
                                                {txt}{help j_robustsingular:F(41, 119) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.2407
                                                {txt}Root MSE          =    {res} .44259

{txt}{ralign 97:(Std. err. adjusted for {res:120} clusters in {res:municipality})}
{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}democracy_pref {c |}{col 33}{res}{space 2}-.0809353{col 45}{space 2} .0475897{col 56}{space 1}   -1.70{col 65}{space 3}0.092{col 73}{space 4}-.1751676{col 86}{space 3}  .013297
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0087757{col 45}{space 2} .0284077{col 56}{space 1}   -0.31{col 65}{space 3}0.758{col 73}{space 4}-.0650258{col 86}{space 3} .0474744
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0532461{col 45}{space 2} .1051577{col 56}{space 1}   -0.51{col 65}{space 3}0.614{col 73}{space 4}-.2614688{col 86}{space 3} .1549766
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0102763{col 45}{space 2} .0619196{col 56}{space 1}   -0.17{col 65}{space 3}0.868{col 73}{space 4}-.1328834{col 86}{space 3} .1123308
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} -.044284{col 45}{space 2} .0474911{col 56}{space 1}   -0.93{col 65}{space 3}0.353{col 73}{space 4}-.1383212{col 86}{space 3} .0497531
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0602879{col 45}{space 2} .0522661{col 56}{space 1}   -1.15{col 65}{space 3}0.251{col 73}{space 4}-.1637799{col 86}{space 3} .0432042
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0322067{col 45}{space 2} .0529135{col 56}{space 1}   -0.61{col 65}{space 3}0.544{col 73}{space 4}-.1369807{col 86}{space 3} .0725673
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0025171{col 45}{space 2} .0587642{col 56}{space 1}    0.04{col 65}{space 3}0.966{col 73}{space 4}-.1138418{col 86}{space 3} .1188761
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0368295{col 45}{space 2} .0732787{col 56}{space 1}   -0.50{col 65}{space 3}0.616{col 73}{space 4}-.1819286{col 86}{space 3} .1082696
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1281344{col 45}{space 2} .1280461{col 56}{space 1}    1.00{col 65}{space 3}0.319{col 73}{space 4}-.1254097{col 86}{space 3} .3816785
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4391704{col 45}{space 2} .2117059{col 56}{space 1}   -2.07{col 65}{space 3}0.040{col 73}{space 4}-.8583692{col 86}{space 3}-.0199715
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0334682{col 45}{space 2} .2747742{col 56}{space 1}    0.12{col 65}{space 3}0.903{col 73}{space 4}-.5106122{col 86}{space 3} .5775486
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0006543{col 45}{space 2} .0044818{col 56}{space 1}    0.15{col 65}{space 3}0.884{col 73}{space 4}-.0082202{col 86}{space 3} .0095287
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000264{col 45}{space 2} .0000489{col 56}{space 1}   -0.54{col 65}{space 3}0.590{col 73}{space 4}-.0001233{col 86}{space 3} .0000704
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0538417{col 45}{space 2} .0954836{col 56}{space 1}   -0.56{col 65}{space 3}0.574{col 73}{space 4}-.2429088{col 86}{space 3} .1352254
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1168811{col 45}{space 2} .1111733{col 56}{space 1}   -1.05{col 65}{space 3}0.295{col 73}{space 4}-.3370154{col 86}{space 3} .1032531
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1497287{col 45}{space 2} .1055851{col 56}{space 1}   -1.42{col 65}{space 3}0.159{col 73}{space 4}-.3587978{col 86}{space 3} .0593405
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0788242{col 45}{space 2} .1081076{col 56}{space 1}   -0.73{col 65}{space 3}0.467{col 73}{space 4} -.292888{col 86}{space 3} .1352396
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0862214{col 45}{space 2} .1060854{col 56}{space 1}   -0.81{col 65}{space 3}0.418{col 73}{space 4}-.2962811{col 86}{space 3} .1238384
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0211949{col 45}{space 2} .0651548{col 56}{space 1}   -0.33{col 65}{space 3}0.746{col 73}{space 4} -.150208{col 86}{space 3} .1078181
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1472519{col 45}{space 2} .0657773{col 56}{space 1}   -2.24{col 65}{space 3}0.027{col 73}{space 4}-.2774975{col 86}{space 3}-.0170064
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} -.182463{col 45}{space 2}  .074976{col 56}{space 1}   -2.43{col 65}{space 3}0.016{col 73}{space 4}-.3309231{col 86}{space 3} -.034003
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2391053{col 45}{space 2} .0681371{col 56}{space 1}   -3.51{col 65}{space 3}0.001{col 73}{space 4}-.3740236{col 86}{space 3} -.104187
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3887333{col 45}{space 2} .0693444{col 56}{space 1}   -5.61{col 65}{space 3}0.000{col 73}{space 4}-.5260421{col 86}{space 3}-.2514245
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2669588{col 45}{space 2} .0701502{col 56}{space 1}   -3.81{col 65}{space 3}0.000{col 73}{space 4}-.4058632{col 86}{space 3}-.1280543
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0346921{col 45}{space 2} .0790938{col 56}{space 1}   -0.44{col 65}{space 3}0.662{col 73}{space 4}-.1913058{col 86}{space 3} .1219216
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2153858{col 45}{space 2} .0715513{col 56}{space 1}   -3.01{col 65}{space 3}0.003{col 73}{space 4}-.3570645{col 86}{space 3} -.073707
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1849568{col 45}{space 2}   .11089{col 56}{space 1}   -1.67{col 65}{space 3}0.098{col 73}{space 4}  -.40453{col 86}{space 3} .0346164
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3520335{col 45}{space 2} .0393317{col 56}{space 1}    8.95{col 65}{space 3}0.000{col 73}{space 4} .2741528{col 86}{space 3} .4299142
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0558895{col 45}{space 2} .0981666{col 56}{space 1}   -0.57{col 65}{space 3}0.570{col 73}{space 4}-.2502692{col 86}{space 3} .1384902
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0059038{col 45}{space 2} .0721482{col 56}{space 1}    0.08{col 65}{space 3}0.935{col 73}{space 4}-.1369568{col 86}{space 3} .1487644
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0441169{col 45}{space 2} .0804529{col 56}{space 1}    0.55{col 65}{space 3}0.584{col 73}{space 4}-.1151878{col 86}{space 3} .2034217
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4476153{col 45}{space 2} .0658107{col 56}{space 1}   -6.80{col 65}{space 3}0.000{col 73}{space 4}-.5779271{col 86}{space 3}-.3173035
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0920522{col 45}{space 2} .0583235{col 56}{space 1}   -1.58{col 65}{space 3}0.117{col 73}{space 4}-.2075386{col 86}{space 3} .0234341
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1571666{col 45}{space 2} .0709395{col 56}{space 1}    2.22{col 65}{space 3}0.029{col 73}{space 4} .0166992{col 86}{space 3}  .297634
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0386624{col 45}{space 2} .0740858{col 56}{space 1}   -0.52{col 65}{space 3}0.603{col 73}{space 4}-.1853597{col 86}{space 3} .1080349
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3842539{col 45}{space 2} .0396661{col 56}{space 1}   -9.69{col 65}{space 3}0.000{col 73}{space 4}-.4627967{col 86}{space 3} -.305711
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1328082{col 45}{space 2} .0692999{col 56}{space 1}    1.92{col 65}{space 3}0.058{col 73}{space 4}-.0044126{col 86}{space 3}  .270029
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1793654{col 45}{space 2} .0647534{col 56}{space 1}   -2.77{col 65}{space 3}0.007{col 73}{space 4}-.3075837{col 86}{space 3}-.0511471
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1133751{col 45}{space 2} .0667076{col 56}{space 1}   -1.70{col 65}{space 3}0.092{col 73}{space 4}-.2454629{col 86}{space 3} .0187127
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0575639{col 45}{space 2} .0956181{col 56}{space 1}   -0.60{col 65}{space 3}0.548{col 73}{space 4}-.2468974{col 86}{space 3} .1317695
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2376027{col 45}{space 2}  .053146{col 56}{space 1}    4.47{col 65}{space 3}0.000{col 73}{space 4} .1323683{col 86}{space 3} .3428371
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1402805{col 45}{space 2} .0526144{col 56}{space 1}    2.67{col 65}{space 3}0.009{col 73}{space 4} .0360988{col 86}{space 3} .2444622
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9787606{col 45}{space 2} .1407562{col 56}{space 1}    6.95{col 65}{space 3}0.000{col 73}{space 4} .7000492{col 86}{space 3} 1.257472
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store prefsystem_2
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. 
. regr cabine_use democracy_pref pp_dummy prefdem_pp, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,802
                                                {txt}F(3, 123)         =  {res}     7.93
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0147
                                                {txt}Root MSE          =    {res} .49347

{txt}{ralign 80:(Std. err. adjusted for {res:124} clusters in {res:municipality})}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}    cabine_use{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
democracy_pref {c |}{col 16}{res}{space 2}-.1215299{col 28}{space 2} .0587935{col 39}{space 1}   -2.07{col 48}{space 3}0.041{col 56}{space 4}-.2379079{col 69}{space 3}-.0051518
{txt}{space 6}pp_dummy {c |}{col 16}{res}{space 2} .2738095{col 28}{space 2} .0946389{col 39}{space 1}    2.89{col 48}{space 3}0.005{col 56}{space 4} .0864777{col 69}{space 3} .4611414
{txt}{space 4}prefdem_pp {c |}{col 16}{res}{space 2}-.1685134{col 28}{space 2} .0980463{col 39}{space 1}   -1.72{col 48}{space 3}0.088{col 56}{space 4}  -.36259{col 69}{space 3} .0255632
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .5357143{col 28}{space 2} .0617693{col 39}{space 1}    8.67{col 48}{space 3}0.000{col 56}{space 4} .4134457{col 69}{space 3} .6579828
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store prefsystem_3
{txt}
{com}. estadd local Controls "No"

{txt}added macro:
           e(Controls) : "{res:No}"

{com}. 
. regr cabine_use democracy_pref pp_dummy prefdem_pp female i.income age age_sq i.education i.TAMUNI i.CCAA, cluster(municipality)

{txt}Linear regression                               Number of obs     = {res}     1,327
                                                {txt}{help j_robustsingular:F(43, 119) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.2461
                                                {txt}Root MSE          =    {res} .44134

{txt}{ralign 97:(Std. err. adjusted for {res:120} clusters in {res:municipality})}
{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 17}democracy_pref {c |}{col 33}{res}{space 2}-.0594136{col 45}{space 2} .0519063{col 56}{space 1}   -1.14{col 65}{space 3}0.255{col 73}{space 4}-.1621933{col 86}{space 3}  .043366
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2} .2321022{col 45}{space 2} .0889863{col 56}{space 1}    2.61{col 65}{space 3}0.010{col 73}{space 4} .0559004{col 86}{space 3}  .408304
{txt}{space 21}prefdem_pp {c |}{col 33}{res}{space 2}-.1474944{col 45}{space 2} .0977133{col 56}{space 1}   -1.51{col 65}{space 3}0.134{col 73}{space 4}-.3409764{col 86}{space 3} .0459876
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0098223{col 45}{space 2} .0285212{col 56}{space 1}   -0.34{col 65}{space 3}0.731{col 73}{space 4}-.0662971{col 86}{space 3} .0466524
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0529028{col 45}{space 2} .1019904{col 56}{space 1}   -0.52{col 65}{space 3}0.605{col 73}{space 4}-.2548539{col 86}{space 3} .1490483
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0008891{col 45}{space 2} .0619713{col 56}{space 1}   -0.01{col 65}{space 3}0.989{col 73}{space 4}-.1235985{col 86}{space 3} .1218203
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0369908{col 45}{space 2}  .047098{col 56}{space 1}   -0.79{col 65}{space 3}0.434{col 73}{space 4}-.1302496{col 86}{space 3}  .056268
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0488753{col 45}{space 2} .0517198{col 56}{space 1}   -0.95{col 65}{space 3}0.347{col 73}{space 4}-.1512857{col 86}{space 3} .0535352
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0201109{col 45}{space 2} .0520246{col 56}{space 1}   -0.39{col 65}{space 3}0.700{col 73}{space 4}-.1231249{col 86}{space 3} .0829031
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0109765{col 45}{space 2}  .059107{col 56}{space 1}    0.19{col 65}{space 3}0.853{col 73}{space 4}-.1060612{col 86}{space 3} .1280142
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0355474{col 45}{space 2}  .074478{col 56}{space 1}   -0.48{col 65}{space 3}0.634{col 73}{space 4}-.1830213{col 86}{space 3} .1119266
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1398819{col 45}{space 2} .1282075{col 56}{space 1}    1.09{col 65}{space 3}0.277{col 73}{space 4}-.1139817{col 86}{space 3} .3937456
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.423323{col 45}{space 2} .2055271{col 56}{space 1}   -2.06{col 65}{space 3}0.042{col 73}{space 4}-.8302871{col 86}{space 3}-.0163589
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0424863{col 45}{space 2} .2914875{col 56}{space 1}    0.15{col 65}{space 3}0.884{col 73}{space 4}-.5346881{col 86}{space 3} .6196606
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0001536{col 45}{space 2} .0044163{col 56}{space 1}    0.03{col 65}{space 3}0.972{col 73}{space 4}-.0085912{col 86}{space 3} .0088984
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000243{col 45}{space 2} .0000484{col 56}{space 1}   -0.50{col 65}{space 3}0.616{col 73}{space 4}-.0001202{col 86}{space 3} .0000716
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0719673{col 45}{space 2} .0971868{col 56}{space 1}   -0.74{col 65}{space 3}0.460{col 73}{space 4} -.264407{col 86}{space 3} .1204723
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1291629{col 45}{space 2} .1132308{col 56}{space 1}   -1.14{col 65}{space 3}0.256{col 73}{space 4}-.3533712{col 86}{space 3} .0950453
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.164344{col 45}{space 2} .1067944{col 56}{space 1}   -1.54{col 65}{space 3}0.126{col 73}{space 4}-.3758075{col 86}{space 3} .0471195
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0932923{col 45}{space 2} .1100557{col 56}{space 1}   -0.85{col 65}{space 3}0.398{col 73}{space 4}-.3112137{col 86}{space 3}  .124629
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1019192{col 45}{space 2} .1090237{col 56}{space 1}   -0.93{col 65}{space 3}0.352{col 73}{space 4}-.3177971{col 86}{space 3} .1139587
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0144295{col 45}{space 2} .0640876{col 56}{space 1}   -0.23{col 65}{space 3}0.822{col 73}{space 4}-.1413294{col 86}{space 3} .1124705
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1384292{col 45}{space 2} .0650732{col 56}{space 1}   -2.13{col 65}{space 3}0.035{col 73}{space 4}-.2672806{col 86}{space 3}-.0095779
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1784314{col 45}{space 2} .0746398{col 56}{space 1}   -2.39{col 65}{space 3}0.018{col 73}{space 4}-.3262256{col 86}{space 3}-.0306372
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2294786{col 45}{space 2} .0671618{col 56}{space 1}   -3.42{col 65}{space 3}0.001{col 73}{space 4}-.3624656{col 86}{space 3}-.0964916
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3823549{col 45}{space 2} .0683166{col 56}{space 1}   -5.60{col 65}{space 3}0.000{col 73}{space 4}-.5176286{col 86}{space 3}-.2470812
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2629658{col 45}{space 2} .0685886{col 56}{space 1}   -3.83{col 65}{space 3}0.000{col 73}{space 4} -.398778{col 86}{space 3}-.1271535
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0210239{col 45}{space 2}  .079933{col 56}{space 1}   -0.26{col 65}{space 3}0.793{col 73}{space 4}-.1792992{col 86}{space 3} .1372515
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2060275{col 45}{space 2} .0724161{col 56}{space 1}   -2.85{col 65}{space 3}0.005{col 73}{space 4}-.3494187{col 86}{space 3}-.0626363
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1783473{col 45}{space 2} .1143569{col 56}{space 1}   -1.56{col 65}{space 3}0.122{col 73}{space 4}-.4047854{col 86}{space 3} .0480908
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3604295{col 45}{space 2} .0404877{col 56}{space 1}    8.90{col 65}{space 3}0.000{col 73}{space 4} .2802599{col 86}{space 3} .4405991
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0548109{col 45}{space 2} .0996341{col 56}{space 1}   -0.55{col 65}{space 3}0.583{col 73}{space 4}-.2520964{col 86}{space 3} .1424746
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0017948{col 45}{space 2} .0691638{col 56}{space 1}    0.03{col 65}{space 3}0.979{col 73}{space 4}-.1351564{col 86}{space 3} .1387461
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0414657{col 45}{space 2} .0750585{col 56}{space 1}    0.55{col 65}{space 3}0.582{col 73}{space 4}-.1071576{col 86}{space 3}  .190089
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} -.434377{col 45}{space 2} .0643159{col 56}{space 1}   -6.75{col 65}{space 3}0.000{col 73}{space 4} -.561729{col 86}{space 3} -.307025
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0898797{col 45}{space 2}  .058549{col 56}{space 1}   -1.54{col 65}{space 3}0.127{col 73}{space 4}-.2058126{col 86}{space 3} .0260532
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1564765{col 45}{space 2} .0739621{col 56}{space 1}    2.12{col 65}{space 3}0.036{col 73}{space 4} .0100242{col 86}{space 3} .3029288
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0297579{col 45}{space 2} .0745729{col 56}{space 1}   -0.40{col 65}{space 3}0.691{col 73}{space 4}-.1774197{col 86}{space 3} .1179039
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3830771{col 45}{space 2} .0393255{col 56}{space 1}   -9.74{col 65}{space 3}0.000{col 73}{space 4}-.4609456{col 86}{space 3}-.3052086
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1298451{col 45}{space 2} .0660844{col 56}{space 1}    1.96{col 65}{space 3}0.052{col 73}{space 4}-.0010087{col 86}{space 3} .2606989
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1662507{col 45}{space 2} .0691477{col 56}{space 1}   -2.40{col 65}{space 3}0.018{col 73}{space 4}  -.30317{col 86}{space 3}-.0293314
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1124704{col 45}{space 2} .0750475{col 56}{space 1}   -1.50{col 65}{space 3}0.137{col 73}{space 4} -.261072{col 86}{space 3} .0361311
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0696765{col 45}{space 2} .0980467{col 56}{space 1}   -0.71{col 65}{space 3}0.479{col 73}{space 4}-.2638188{col 86}{space 3} .1244658
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2388749{col 45}{space 2} .0546371{col 56}{space 1}    4.37{col 65}{space 3}0.000{col 73}{space 4}  .130688{col 86}{space 3} .3470619
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1254754{col 45}{space 2} .0530642{col 56}{space 1}    2.36{col 65}{space 3}0.020{col 73}{space 4}  .020403{col 86}{space 3} .2305479
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9606181{col 45}{space 2}  .142187{col 56}{space 1}    6.76{col 65}{space 3}0.000{col 73}{space 4} .6790736{col 86}{space 3} 1.242163
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store prefsystem_4
{txt}
{com}. estadd local Controls "Yes"

{txt}added macro:
           e(Controls) : "{res:Yes}"

{com}. 
. * Make table
. esttab prefsystem_1 prefsystem_2 prefsystem_3 prefsystem_4 using 03_tables/tablef3.tex, tex se replace  keep (democracy_pref pp_dummy prefdem_pp) coeflabels (democracy_pref "Prefers democracy" pp_dummy "PP voter" prefdem_pp "Prefer dem x PP voter") star(* 0.10 ** 0.05 *** 0.01) s(Controls, label("Controls")) nomtitles addnotes("Standard errors are clustered by municipality" "The outcome variable is a dummy for whether each respondent used a private" "voting booth to cast their vote in the general election of November 2019" "Models 2 and 4 include controls for income, education, age, age squared, size of" "respondent's municipality, and a dummy for respondents identifying as female")
{res}{txt}(output written to {browse  `"03_tables/tablef3.tex"'})

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured1_1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. * Fake model to get the dataset started
. reg pp_voteshare turnout 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}   225,903
{txt}{hline 13}{c +}{hline 34}   F(1, 225901)    = {res}   485.86
{txt}       Model {c |} {res} 153061.286         1  153061.286   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 71165552.8   225,901  315.029826   {txt}R-squared       ={res}    0.0021
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0021
{txt}       Total {c |} {res} 71318614.1   225,902  315.705988   {txt}Root MSE        =   {res} 17.749

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}pp_voteshare{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}turnout {c |}{col 14}{res}{space 2} .0629035{col 26}{space 2} .0028538{col 37}{space 1}   22.04{col 46}{space 3}0.000{col 54}{space 4} .0573102{col 67}{space 3} .0684968
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 26.25163{col 26}{space 2} .1646255{col 37}{space 1}  159.46{col 46}{space 3}0.000{col 54}{space 4} 25.92897{col 67}{space 3}  26.5743
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regsave turnout using 01_data/other_outcomes.dta, ci replace addlabel (Outcome, fake, Model, 0) 
{txt}{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * Turnout
. reghdfe turnout post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 31824 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   115,458
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  57728{txt}){col 67}= {res}  62304.34
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9274
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8548
{txt}{col 51}Within R-sq.{col 67}= {res}    0.8395
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    57,729{txt}{col 51}Root MSE{col 67}= {res}    4.8480

{txt}{ralign 84:(Std. err. adjusted for {res:57,729} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}           turnout{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-.1599082{col 32}{space 2} .0371974{col 43}{space 1}   -4.30{col 52}{space 3}0.000{col 60}{space 4}-.2328153{col 73}{space 3}-.0870011
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 19.05648{col 32}{space 2} .0531147{col 43}{space 1}  358.78{col 52}{space 3}0.000{col 60}{space 4} 18.95238{col 73}{space 3} 19.16059
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 2.329691{col 32}{space 2} .3869431{col 43}{space 1}    6.02{col 52}{space 3}0.000{col 60}{space 4}  1.57128{col 73}{space 3} 3.088101
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.173203{col 32}{space 2} .7900031{col 43}{space 1}   -2.75{col 52}{space 3}0.006{col 60}{space 4}-3.721613{col 73}{space 3}-.6247929
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 52.31787{col 32}{space 2} .0142676{col 43}{space 1} 3666.90{col 52}{space 3}0.000{col 60}{space 4}  52.2899{col 73}{space 3} 52.34583
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    57729{col 38}{space 1}    57729{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, Turnout, Model, Model 1)
{txt}{p 0 7 2}
(note: variable
{bf:Model} was byte in the using data, but will be
str7 now)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * PSOE
. reghdfe psoe_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 34983 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   102,210
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  51104{txt}){col 67}= {res}  16593.72
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9198
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8397
{txt}{col 51}Within R-sq.{col 67}= {res}    0.5661
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    51,105{txt}{col 51}Root MSE{col 67}= {res}    5.4079

{txt}{ralign 84:(Std. err. adjusted for {res:51,105} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}    psoe_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} 6.320677{col 32}{space 2} .0588928{col 43}{space 1}  107.33{col 52}{space 3}0.000{col 60}{space 4} 6.205246{col 73}{space 3} 6.436107
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  3.36237{col 32}{space 2} .0719795{col 43}{space 1}   46.71{col 52}{space 3}0.000{col 60}{space 4} 3.221289{col 73}{space 3}  3.50345
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-4.521106{col 32}{space 2} .4829701{col 43}{space 1}   -9.36{col 52}{space 3}0.000{col 60}{space 4}-5.467733{col 73}{space 3} -3.57448
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} 1.550474{col 32}{space 2} .8375237{col 43}{space 1}    1.85{col 52}{space 3}0.064{col 60}{space 4}-.0910815{col 73}{space 3} 3.192029
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 24.18194{col 32}{space 2} .0169151{col 43}{space 1} 1429.60{col 52}{space 3}0.000{col 60}{space 4} 24.14879{col 73}{space 3}  24.2151
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    51105{col 38}{space 1}    51105{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, PSOE voteshare, Model, Model 1)
{txt}{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * Null votes
. reghdfe null_share post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 31793 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   115,514
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  57756{txt}){col 67}= {res}   4971.65
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.6719
{txt}{col 51}Adj R-squared{col 67}= {res}    0.3437
{txt}{col 51}Within R-sq.{col 67}= {res}    0.2502
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    57,757{txt}{col 51}Root MSE{col 67}= {res}    1.0769

{txt}{ralign 84:(Std. err. adjusted for {res:57,757} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        null_share{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} -.492655{col 32}{space 2} .0060073{col 43}{space 1}  -82.01{col 52}{space 3}0.000{col 60}{space 4}-.5044294{col 73}{space 3}-.4808806
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.5141124{col 32}{space 2} .0106547{col 43}{space 1}  -48.25{col 52}{space 3}0.000{col 60}{space 4}-.5349956{col 73}{space 3}-.4932291
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.5073597{col 32}{space 2} .1437086{col 43}{space 1}   -3.53{col 52}{space 3}0.000{col 60}{space 4}-.7890293{col 73}{space 3}-.2256901
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} .5641325{col 32}{space 2} .2447356{col 43}{space 1}    2.31{col 52}{space 3}0.021{col 60}{space 4} .0844495{col 73}{space 3} 1.043816
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.620018{col 32}{space 2} .0031685{col 43}{space 1}  511.28{col 52}{space 3}0.000{col 60}{space 4} 1.613808{col 73}{space 3} 1.626229
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    57757{col 38}{space 1}    57757{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, Null votes, Model, Model 1)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str10}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * White votes
. reghdfe white_share post##ep##ciutadella if period > 1, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 31793 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   115,514
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  57756{txt}){col 67}= {res}   4972.03
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.6720
{txt}{col 51}Adj R-squared{col 67}= {res}    0.3440
{txt}{col 51}Within R-sq.{col 67}= {res}    0.2503
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    57,757{txt}{col 51}Root MSE{col 67}= {res}    1.0770

{txt}{ralign 84:(Std. err. adjusted for {res:57,757} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}       white_share{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} -.492655{col 32}{space 2} .0060073{col 43}{space 1}  -82.01{col 52}{space 3}0.000{col 60}{space 4}-.5044294{col 73}{space 3}-.4808806
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.5141124{col 32}{space 2} .0106547{col 43}{space 1}  -48.25{col 52}{space 3}0.000{col 60}{space 4}-.5349956{col 73}{space 3}-.4932291
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.130555{col 32}{space 2}  .218341{col 43}{space 1}   -5.18{col 52}{space 3}0.000{col 60}{space 4}-1.558505{col 73}{space 3}-.7026058
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} 1.141717{col 32}{space 2} .3217916{col 43}{space 1}    3.55{col 52}{space 3}0.000{col 60}{space 4} .5110037{col 73}{space 3}  1.77243
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.620994{col 32}{space 2} .0031689{col 43}{space 1}  511.52{col 52}{space 3}0.000{col 60}{space 4} 1.614783{col 73}{space 3} 1.627205
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    57757{col 38}{space 1}    57757{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, White votes, Model, Model 1)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str11}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * Turnout
. reghdfe turnout post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26175 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,025
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  74345{txt}){col 67}= {res}  84621.95
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9010
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8424
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7671
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,346{txt}{col 51}Root MSE{col 67}= {res}    5.1743

{txt}{ralign 84:(Std. err. adjusted for {res:74,346} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}           turnout{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-.0116717{col 32}{space 2} .0404552{col 43}{space 1}   -0.29{col 52}{space 3}0.773{col 60}{space 4}-.0909638{col 73}{space 3} .0676204
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 18.63451{col 32}{space 2} .0516189{col 43}{space 1}  361.00{col 52}{space 3}0.000{col 60}{space 4} 18.53333{col 73}{space 3} 18.73568
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1282287{col 32}{space 2} .4232328{col 43}{space 1}   -0.30{col 52}{space 3}0.762{col 60}{space 4}-.9577632{col 73}{space 3} .7013059
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} 1.110535{col 32}{space 2} .7304916{col 43}{space 1}    1.52{col 52}{space 3}0.128{col 60}{space 4}-.3212255{col 73}{space 3} 2.542295
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 51.61344{col 32}{space 2} .0091663{col 43}{space 1} 5630.81{col 52}{space 3}0.000{col 60}{space 4} 51.59547{col 73}{space 3}  51.6314
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74346{col 38}{space 1}    74346{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, Turnout, Model, Model 2)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str7}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * PSOE
. reghdfe psoe_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 27044 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   188,048
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  71382{txt}){col 67}= {res}   1793.10
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.7743
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6361
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0357
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    71,383{txt}{col 51}Root MSE{col 67}= {res}    8.6859

{txt}{ralign 84:(Std. err. adjusted for {res:71,383} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}    psoe_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} 4.524834{col 32}{space 2} .0669329{col 43}{space 1}   67.60{col 52}{space 3}0.000{col 60}{space 4} 4.393646{col 73}{space 3} 4.656022
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-2.644063{col 32}{space 2} .0764808{col 43}{space 1}  -34.57{col 52}{space 3}0.000{col 60}{space 4}-2.793965{col 73}{space 3}-2.494161
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-4.650142{col 32}{space 2} .4871586{col 43}{space 1}   -9.55{col 52}{space 3}0.000{col 60}{space 4}-5.604972{col 73}{space 3}-3.695313
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-.1374131{col 32}{space 2} .8278103{col 43}{space 1}   -0.17{col 52}{space 3}0.868{col 60}{space 4}-1.759919{col 73}{space 3} 1.485093
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 29.98934{col 32}{space 2} .0108453{col 43}{space 1} 2765.20{col 52}{space 3}0.000{col 60}{space 4} 29.96808{col 73}{space 3} 30.01059
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    71383{col 38}{space 1}    71383{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, PSOE voteshare, Model, Model 2)
{txt}{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * Null votes
. reghdfe null_share post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26129 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,146
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  74390{txt}){col 67}= {res}   5487.08
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4248
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0845
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0555
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,391{txt}{col 51}Root MSE{col 67}= {res}    1.1732

{txt}{ralign 84:(Std. err. adjusted for {res:74,391} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        null_share{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} -.781051{col 32}{space 2} .0056193{col 43}{space 1} -138.99{col 52}{space 3}0.000{col 60}{space 4}-.7920649{col 73}{space 3}-.7700372
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4838434{col 32}{space 2}  .008123{col 43}{space 1}   59.56{col 52}{space 3}0.000{col 60}{space 4} .4679223{col 73}{space 3} .4997644
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1693498{col 32}{space 2} .1265599{col 43}{space 1}   -1.34{col 52}{space 3}0.181{col 60}{space 4}-.4174067{col 73}{space 3} .0787072
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} .0744123{col 32}{space 2} .2131055{col 43}{space 1}    0.35{col 52}{space 3}0.727{col 60}{space 4}-.3432737{col 73}{space 3} .4920983
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.226293{col 32}{space 2} .0016157{col 43}{space 1}  758.97{col 52}{space 3}0.000{col 60}{space 4} 1.223126{col 73}{space 3}  1.22946
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74391{col 38}{space 1}    74391{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, Null votes, Model, Model 2)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str10}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * White votes
. reghdfe white_share post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26129 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,146
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  74390{txt}){col 67}= {res}   5496.74
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4255
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0856
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0558
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,391{txt}{col 51}Root MSE{col 67}= {res}    1.1733

{txt}{ralign 84:(Std. err. adjusted for {res:74,391} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}       white_share{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2} -.781051{col 32}{space 2} .0056193{col 43}{space 1} -138.99{col 52}{space 3}0.000{col 60}{space 4}-.7920649{col 73}{space 3}-.7700372
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4838434{col 32}{space 2}  .008123{col 43}{space 1}   59.56{col 52}{space 3}0.000{col 60}{space 4} .4679223{col 73}{space 3} .4997644
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.081618{col 32}{space 2}  .206961{col 43}{space 1}   -5.23{col 52}{space 3}0.000{col 60}{space 4}-1.487261{col 73}{space 3}-.6759758
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} .4291695{col 32}{space 2} .2991733{col 43}{space 1}    1.43{col 52}{space 3}0.151{col 60}{space 4} -.157209{col 73}{space 3} 1.015548
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.227474{col 32}{space 2}  .001616{col 43}{space 1}  759.57{col 52}{space 3}0.000{col 60}{space 4} 1.224307{col 73}{space 3} 1.230642
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74391{col 38}{space 1}    74391{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, White votes, Model, Model 2)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str11}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * Turnout
. reghdfe turnout post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26175 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,025
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  74345{txt}){col 67}= {res}  68837.99
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9011
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8425
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7672
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,346{txt}{col 51}Root MSE{col 67}= {res}    5.1730

{txt}{ralign 84:(Std. err. adjusted for {res:74,346} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}           turnout{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-.1344273{col 32}{space 2} .0453118{col 43}{space 1}   -2.97{col 52}{space 3}0.003{col 60}{space 4}-.2232382{col 73}{space 3}-.0456163
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 18.65512{col 32}{space 2} .0518217{col 43}{space 1}  359.99{col 52}{space 3}0.000{col 60}{space 4} 18.55355{col 73}{space 3} 18.75669
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1221533{col 32}{space 2} .4232434{col 43}{space 1}   -0.29{col 52}{space 3}0.773{col 60}{space 4}-.9517086{col 73}{space 3} .7074021
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} 1.089922{col 32}{space 2} .7305003{col 43}{space 1}    1.49{col 52}{space 3}0.136{col 60}{space 4}-.3418561{col 73}{space 3} 2.521699
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-.2333604{col 32}{space 2}  .028256{col 43}{space 1}   -8.26{col 52}{space 3}0.000{col 60}{space 4}-.2887421{col 73}{space 3}-.1779787
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 51.72298{col 32}{space 2} .0173612{col 43}{space 1} 2979.23{col 52}{space 3}0.000{col 60}{space 4} 51.68895{col 73}{space 3} 51.75701
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74346{col 38}{space 1}    74346{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, Turnout, Model, Model 3)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str7}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * PSOE
. reghdfe psoe_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 27044 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   188,048
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  71382{txt}){col 67}= {res}  22270.36
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8765
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8009
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4723
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    71,383{txt}{col 51}Root MSE{col 67}= {res}    6.4251

{txt}{ralign 84:(Std. err. adjusted for {res:71,383} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}    psoe_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-1.606054{col 32}{space 2} .0744824{col 43}{space 1}  -21.56{col 52}{space 3}0.000{col 60}{space 4} -1.75204{col 73}{space 3}-1.460069
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.650374{col 32}{space 2} .0756148{col 43}{space 1}  -21.83{col 52}{space 3}0.000{col 60}{space 4}-1.798579{col 73}{space 3} -1.50217
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-4.376381{col 32}{space 2} .4871712{col 43}{space 1}   -8.98{col 52}{space 3}0.000{col 60}{space 4}-5.331235{col 73}{space 3}-3.421527
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-1.131101{col 32}{space 2} .8277357{col 43}{space 1}   -1.37{col 52}{space 3}0.172{col 60}{space 4}-2.753461{col 73}{space 3} .4912584
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-11.71425{col 32}{space 2} .0397514{col 43}{space 1} -294.69{col 52}{space 3}0.000{col 60}{space 4}-11.79217{col 73}{space 3}-11.63634
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 35.51786{col 32}{space 2} .0228602{col 43}{space 1} 1553.70{col 52}{space 3}0.000{col 60}{space 4} 35.47306{col 73}{space 3} 35.56267
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    71383{col 38}{space 1}    71383{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, PSOE voteshare, Model, Model 3)
{txt}{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * Null votes
. reghdfe null_share post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26129 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,146
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  74390{txt}){col 67}= {res}   6134.97
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4728
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1609
{txt}{col 51}Within R-sq.{col 67}= {res}    0.1343
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,391{txt}{col 51}Root MSE{col 67}= {res}    1.1231

{txt}{ralign 84:(Std. err. adjusted for {res:74,391} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}        null_share{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-.4145292{col 32}{space 2} .0073435{col 43}{space 1}  -56.45{col 52}{space 3}0.000{col 60}{space 4}-.4289224{col 73}{space 3} -.400136
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4222644{col 32}{space 2} .0083138{col 43}{space 1}   50.79{col 52}{space 3}0.000{col 60}{space 4} .4059694{col 73}{space 3} .4385594
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1875046{col 32}{space 2} .1265668{col 43}{space 1}   -1.48{col 52}{space 3}0.138{col 60}{space 4} -.435575{col 73}{space 3} .0605658
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} .1359912{col 32}{space 2} .2131129{col 43}{space 1}    0.64{col 52}{space 3}0.523{col 60}{space 4}-.2817092{col 73}{space 3} .5536916
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}  .696734{col 32}{space 2} .0076201{col 43}{space 1}   91.43{col 52}{space 3}0.000{col 60}{space 4} .6817986{col 73}{space 3} .7116694
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  .899233{col 32}{space 2} .0036685{col 43}{space 1}  245.12{col 52}{space 3}0.000{col 60}{space 4} .8920428{col 73}{space 3} .9064232
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74391{col 38}{space 1}    74391{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, Null votes, Model, Model 3)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str10}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
. * White votes
. reghdfe white_share post##ep##ciutadella i.period, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{res}{txt}(dropped 26129 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,146
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  74390{txt}){col 67}= {res}   6139.30
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.4733
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1617
{txt}{col 51}Within R-sq.{col 67}= {res}    0.1344
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,391{txt}{col 51}Root MSE{col 67}= {res}    1.1234

{txt}{ralign 84:(Std. err. adjusted for {res:74,391} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}       white_share{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-.4149258{col 32}{space 2} .0073437{col 43}{space 1}  -56.50{col 52}{space 3}0.000{col 60}{space 4}-.4293194{col 73}{space 3}-.4005321
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .422331{col 32}{space 2} .0083137{col 43}{space 1}   50.80{col 52}{space 3}0.000{col 60}{space 4} .4060361{col 73}{space 3} .4386259
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.099754{col 32}{space 2}  .206965{col 43}{space 1}   -5.31{col 52}{space 3}0.000{col 60}{space 4}-1.505404{col 73}{space 3}-.6941031
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} .4906818{col 32}{space 2}  .299179{col 43}{space 1}    1.64{col 52}{space 3}0.101{col 60}{space 4}-.0957077{col 73}{space 3} 1.077071
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2} .6959802{col 32}{space 2} .0076216{col 43}{space 1}   91.32{col 52}{space 3}0.000{col 60}{space 4} .6810418{col 73}{space 3} .7109186
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  .900768{col 32}{space 2} .0036694{col 43}{space 1}  245.48{col 52}{space 3}0.000{col 60}{space 4}  .893576{col 73}{space 3}   .90796
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74391{col 38}{space 1}    74391{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append addlabel (Outcome, White votes, Model, Model 3)
{txt}{p 0 7 2}
(variable
{bf:Outcome} was {bf:str11}, now {bf:str14} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/other_outcomes.dta{rm}
saved
{p_end}

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured2_1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/whole_spain.dta, clear
{txt}
{com}. 
. * Fake model to get the dataset started
. reg ep post 

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}   231,586
{txt}{hline 13}{c +}{hline 34}   F(1, 231584)    = {res}    46.55
{txt}       Model {c |} {res} 9.27768029         1  9.27768029   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 46155.9124   231,584  .199305273   {txt}R-squared       ={res}    0.0002
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0002
{txt}       Total {c |} {res} 46165.1901   231,585  .199344474   {txt}Root MSE        =   {res} .44644

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          ep{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}post {c |}{col 14}{res}{space 2}  .013264{col 26}{space 2} .0019441{col 37}{space 1}    6.82{col 46}{space 3}0.000{col 54}{space 4} .0094537{col 67}{space 3} .0170744
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7204182{col 26}{space 2} .0011513{col 37}{space 1}  625.76{col 46}{space 3}0.000{col 54}{space 4} .7181617{col 67}{space 3} .7226746
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regsave post using 01_data/jackknives_ddd.dta, ci replace addlabel (Region, 0, Model, 0)
{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}

{com}. 
. 
. forvalues x = 1/3 {c -(}
{txt}  2{com}. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & CODCCAA != `x', absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{txt}  3{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci append addlabel (Region, `x', Model, Model 1)
{txt}  4{com}.         
. reghdfe pp_voteshare post##ep##ciutadella if CODCCAA != `x', absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{txt}  5{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci append addlabel (Region, `x', Model, Model 2)
{txt}  6{com}. 
. 
. reghdfe pp_voteshare post##ep##ciutadella i.period if CODCCAA != `x', absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{txt}  7{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci append addlabel (Region, `x', Model, Model 3)
{txt}  8{com}. {c )-}
{res}{txt}(dropped 26320 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   100,962
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  50480{txt}){col 67}= {res}  10876.05
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9450
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8900
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4567
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    50,481{txt}{col 51}Root MSE{col 67}= {res}    4.9539

{txt}{ralign 84:(Std. err. adjusted for {res:50,481} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}  -6.1091{col 32}{space 2} .0595068{col 43}{space 1} -102.66{col 52}{space 3}0.000{col 60}{space 4}-6.225734{col 73}{space 3}-5.992466
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.4604574{col 32}{space 2} .0696828{col 43}{space 1}   -6.61{col 52}{space 3}0.000{col 60}{space 4}-.5970366{col 73}{space 3}-.3238783
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.155187{col 32}{space 2} .6930653{col 43}{space 1}    1.67{col 52}{space 3}0.096{col 60}{space 4}-.2032285{col 73}{space 3} 2.513603
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.645043{col 32}{space 2} 1.121844{col 43}{space 1}   -2.36{col 52}{space 3}0.018{col 60}{space 4} -4.84387{col 73}{space 3} -.446216
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.59381{col 32}{space 2} .0155906{col 43}{space 1} 1769.90{col 52}{space 3}0.000{col 60}{space 4} 27.56325{col 73}{space 3} 27.62437
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    50481{col 38}{space 1}    50481{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 7 2}
(note: variable
{bf:Model} was byte in the using data, but will be
str7 now)
{p_end}
{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 21207 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   173,515
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  64174{txt}){col 67}= {res}  41088.51
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8251
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7224
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4352
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    64,175{txt}{col 51}Root MSE{col 67}= {res}    9.3849

{txt}{ralign 84:(Std. err. adjusted for {res:64,175} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.66086{col 32}{space 2} .0713213{col 43}{space 1} -177.52{col 52}{space 3}0.000{col 60}{space 4}-12.80065{col 73}{space 3}-12.52107
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} -1.82577{col 32}{space 2} .0817103{col 43}{space 1}  -22.34{col 52}{space 3}0.000{col 60}{space 4}-1.985922{col 73}{space 3}-1.665617
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .145158{col 32}{space 2} .5897541{col 43}{space 1}    0.25{col 52}{space 3}0.806{col 60}{space 4}-1.010761{col 73}{space 3} 1.301077
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-1.655556{col 32}{space 2} 1.008673{col 43}{space 1}   -1.64{col 52}{space 3}0.101{col 60}{space 4}-3.632556{col 73}{space 3} .3214439
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.71174{col 32}{space 2} .0122634{col 43}{space 1} 2830.51{col 52}{space 3}0.000{col 60}{space 4}  34.6877{col 73}{space 3} 34.73577
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    64175{col 38}{space 1}    64175{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 21207 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   173,515
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  64174{txt}){col 67}= {res}  45322.07
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9174
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8689
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7333
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    64,175{txt}{col 51}Root MSE{col 67}= {res}    6.4494

{txt}{ralign 84:(Std. err. adjusted for {res:64,175} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-19.99006{col 32}{space 2}  .078737{col 43}{space 1} -253.88{col 52}{space 3}0.000{col 60}{space 4}-20.14438{col 73}{space 3}-19.83574
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.6709924{col 32}{space 2} .0790713{col 43}{space 1}   -8.49{col 52}{space 3}0.000{col 60}{space 4}-.8259723{col 73}{space 3}-.5160125
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .497304{col 32}{space 2} .5895679{col 43}{space 1}    0.84{col 52}{space 3}0.399{col 60}{space 4}-.6582496{col 73}{space 3} 1.652858
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.810333{col 32}{space 2}  1.00847{col 43}{space 1}   -2.79{col 52}{space 3}0.005{col 60}{space 4}-4.786936{col 73}{space 3}-.8337302
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2} -13.9541{col 32}{space 2} .0397543{col 43}{space 1} -351.01{col 52}{space 3}0.000{col 60}{space 4}-14.03202{col 73}{space 3}-13.87618
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.31711{col 32}{space 2} .0260045{col 43}{space 1} 1588.84{col 52}{space 3}0.000{col 60}{space 4} 41.26614{col 73}{space 3} 41.36808
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    64175{col 38}{space 1}    64175{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30896 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   113,892
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  56945{txt}){col 67}= {res}  10146.28
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9375
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8749
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4019
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    56,946{txt}{col 51}Root MSE{col 67}= {res}    5.2475

{txt}{ralign 84:(Std. err. adjusted for {res:56,946} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.205263{col 32}{space 2} .0658088{col 43}{space 1}  -94.29{col 52}{space 3}0.000{col 60}{space 4}-6.334249{col 73}{space 3}-6.076277
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1801643{col 32}{space 2} .0740343{col 43}{space 1}    2.43{col 52}{space 3}0.015{col 60}{space 4} .0350566{col 73}{space 3}  .325272
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  1.25135{col 32}{space 2} .6936325{col 43}{space 1}    1.80{col 52}{space 3}0.071{col 60}{space 4} -.108174{col 73}{space 3} 2.610873
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.285665{col 32}{space 2} 1.122119{col 43}{space 1}   -2.93{col 52}{space 3}0.003{col 60}{space 4}-5.485024{col 73}{space 3}-1.086305
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  27.3271{col 32}{space 2} .0155489{col 43}{space 1} 1757.50{col 52}{space 3}0.000{col 60}{space 4} 27.29663{col 73}{space 3} 27.35758
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    56946{col 38}{space 1}    56946{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25212 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   196,861
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  73103{txt}){col 67}= {res}  42819.59
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8197
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7132
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4200
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    73,104{txt}{col 51}Root MSE{col 67}= {res}    9.4969

{txt}{ralign 84:(Std. err. adjusted for {res:73,104} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-13.04172{col 32}{space 2} .0717777{col 43}{space 1} -181.70{col 52}{space 3}0.000{col 60}{space 4}-13.18241{col 73}{space 3}-12.90104
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.8898019{col 32}{space 2} .0810207{col 43}{space 1}  -10.98{col 52}{space 3}0.000{col 60}{space 4}-1.048602{col 73}{space 3}-.7310016
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .5260166{col 32}{space 2} .5898081{col 43}{space 1}    0.89{col 52}{space 3}0.372{col 60}{space 4}-.6300052{col 73}{space 3} 1.682038
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.591523{col 32}{space 2} 1.008615{col 43}{space 1}   -2.57{col 52}{space 3}0.010{col 60}{space 4}-4.568405{col 73}{space 3}-.6146418
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.54046{col 32}{space 2} .0118173{col 43}{space 1} 2922.87{col 52}{space 3}0.000{col 60}{space 4}  34.5173{col 73}{space 3} 34.56362
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    73104{col 38}{space 1}    73104{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25212 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   196,861
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  73103{txt}){col 67}= {res}  49566.31
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9145
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8639
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7249
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    73,104{txt}{col 51}Root MSE{col 67}= {res}    6.5409

{txt}{ralign 84:(Std. err. adjusted for {res:73,104} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.47706{col 32}{space 2} .0770446{col 43}{space 1} -265.78{col 52}{space 3}0.000{col 60}{space 4}-20.62807{col 73}{space 3}-20.32606
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3218699{col 32}{space 2} .0782338{col 43}{space 1}    4.11{col 52}{space 3}0.000{col 60}{space 4}  .168532{col 73}{space 3} .4752078
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .9006817{col 32}{space 2}  .589596{col 43}{space 1}    1.53{col 52}{space 3}0.127{col 60}{space 4}-.2549245{col 73}{space 3} 2.056288
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.803195{col 32}{space 2} 1.008402{col 43}{space 1}   -3.77{col 52}{space 3}0.000{col 60}{space 4}-5.779659{col 73}{space 3}-1.826731
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.12135{col 32}{space 2} .0374732{col 43}{space 1} -376.84{col 52}{space 3}0.000{col 60}{space 4} -14.1948{col 73}{space 3}-14.04791
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.20138{col 32}{space 2} .0243002{col 43}{space 1} 1695.52{col 52}{space 3}0.000{col 60}{space 4} 41.15375{col 73}{space 3} 41.24901
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    73104{col 38}{space 1}    73104{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 31275 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   115,170
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  57584{txt}){col 67}= {res}  10346.29
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9372
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8744
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4052
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    57,585{txt}{col 51}Root MSE{col 67}= {res}    5.2573

{txt}{ralign 84:(Std. err. adjusted for {res:57,585} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.198538{col 32}{space 2} .0646584{col 43}{space 1}  -95.87{col 52}{space 3}0.000{col 60}{space 4}-6.325268{col 73}{space 3}-6.071807
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .091051{col 32}{space 2}  .073104{col 43}{space 1}    1.25{col 52}{space 3}0.213{col 60}{space 4}-.0522333{col 73}{space 3} .2343353
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.244624{col 32}{space 2} .6935241{col 43}{space 1}    1.79{col 52}{space 3}0.073{col 60}{space 4}-.1146864{col 73}{space 3} 2.603935
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.196551{col 32}{space 2} 1.122058{col 43}{space 1}   -2.85{col 52}{space 3}0.004{col 60}{space 4}-5.395791{col 73}{space 3}-.9973123
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.54834{col 32}{space 2} .0154914{col 43}{space 1} 1778.30{col 52}{space 3}0.000{col 60}{space 4} 27.51798{col 73}{space 3} 27.57871
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    57585{col 38}{space 1}    57585{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25589 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   199,190
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  74003{txt}){col 67}= {res}  43664.90
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8210
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7152
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4235
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,004{txt}{col 51}Root MSE{col 67}= {res}    9.4467

{txt}{ralign 84:(Std. err. adjusted for {res:74,004} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-13.17008{col 32}{space 2} .0699255{col 43}{space 1} -188.34{col 52}{space 3}0.000{col 60}{space 4}-13.30713{col 73}{space 3}-13.03302
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.7360907{col 32}{space 2} .0792931{col 43}{space 1}   -9.28{col 52}{space 3}0.000{col 60}{space 4}-.8915048{col 73}{space 3}-.5806766
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .6543699{col 32}{space 2} .5895855{col 43}{space 1}    1.11{col 52}{space 3}0.267{col 60}{space 4}-.5012153{col 73}{space 3} 1.809955
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.745235{col 32}{space 2} 1.008477{col 43}{space 1}   -2.72{col 52}{space 3}0.006{col 60}{space 4}-4.721846{col 73}{space 3} -.768623
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.72445{col 32}{space 2} .0116998{col 43}{space 1} 2967.94{col 52}{space 3}0.000{col 60}{space 4} 34.70151{col 73}{space 3} 34.74738
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74004{col 38}{space 1}    74004{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25589 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   199,190
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  74003{txt}){col 67}= {res}  50607.88
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9152
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8650
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7268
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,004{txt}{col 51}Root MSE{col 67}= {res}    6.5033

{txt}{ralign 84:(Std. err. adjusted for {res:74,004} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.57534{col 32}{space 2} .0748436{col 43}{space 1} -274.91{col 52}{space 3}0.000{col 60}{space 4}-20.72204{col 73}{space 3}-20.42865
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4847417{col 32}{space 2} .0764415{col 43}{space 1}    6.34{col 52}{space 3}0.000{col 60}{space 4} .3349167{col 73}{space 3} .6345668
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.027387{col 32}{space 2} .5893718{col 43}{space 1}    1.74{col 52}{space 3}0.081{col 60}{space 4}-.1277797{col 73}{space 3} 2.182553
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.966067{col 32}{space 2} 1.008264{col 43}{space 1}   -3.93{col 52}{space 3}0.000{col 60}{space 4}-5.942261{col 73}{space 3}-1.989873
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2} -14.0645{col 32}{space 2} .0370377{col 43}{space 1} -379.74{col 52}{space 3}0.000{col 60}{space 4}-14.13709{col 73}{space 3}-13.99191
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  41.3506{col 32}{space 2}  .023923{col 43}{space 1} 1728.49{col 52}{space 3}0.000{col 60}{space 4} 41.30372{col 73}{space 3} 41.39749
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74004{col 38}{space 1}    74004{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}

{com}. 
. * CCAA code 4 is Balearic Islands, which is why I don't remove it
. 
. forvalues x = 5/19 {c -(}
{txt}  2{com}. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & CODCCAA != `x', absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{txt}  3{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci append addlabel (Region, `x', Model, Model 1)
{txt}  4{com}.         
. reghdfe pp_voteshare post##ep##ciutadella if CODCCAA != `x', absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{txt}  5{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci append addlabel (Region, `x', Model, Model 2)
{txt}  6{com}. 
. reghdfe pp_voteshare post##ep##ciutadella i.period if CODCCAA != `x', absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
{txt}  7{com}. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci append addlabel (Region, `x', Model, Model 3)
{txt}  8{com}. {c )-}
{res}{txt}(dropped 30179 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   113,994
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  56996{txt}){col 67}= {res}   9964.58
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9378
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8756
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3975
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    56,997{txt}{col 51}Root MSE{col 67}= {res}    5.2603

{txt}{ralign 84:(Std. err. adjusted for {res:56,997} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.075802{col 32}{space 2} .0651298{col 43}{space 1}  -93.29{col 52}{space 3}0.000{col 60}{space 4}-6.203457{col 73}{space 3}-5.948147
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0501689{col 32}{space 2} .0735687{col 43}{space 1}    0.68{col 52}{space 3}0.495{col 60}{space 4}-.0940261{col 73}{space 3} .1943639
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.121889{col 32}{space 2} .6935684{col 43}{space 1}    1.62{col 52}{space 3}0.106{col 60}{space 4}-.2375093{col 73}{space 3} 2.481287
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.155669{col 32}{space 2} 1.122088{col 43}{space 1}   -2.81{col 52}{space 3}0.005{col 60}{space 4}-5.354969{col 73}{space 3}-.9563696
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.58017{col 32}{space 2} .0155798{col 43}{space 1} 1770.25{col 52}{space 3}0.000{col 60}{space 4} 27.54963{col 73}{space 3} 27.61071
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    56997{col 38}{space 1}    56997{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25107 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   196,192
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  72789{txt}){col 67}= {res}  42737.29
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8238
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7198
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4178
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    72,790{txt}{col 51}Root MSE{col 67}= {res}    9.3963

{txt}{ralign 84:(Std. err. adjusted for {res:72,790} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.89719{col 32}{space 2} .0712886{col 43}{space 1} -180.92{col 52}{space 3}0.000{col 60}{space 4}-13.03692{col 73}{space 3}-12.75747
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.8087133{col 32}{space 2} .0803086{col 43}{space 1}  -10.07{col 52}{space 3}0.000{col 60}{space 4}-.9661179{col 73}{space 3}-.6513088
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3814844{col 32}{space 2} .5897488{col 43}{space 1}    0.65{col 52}{space 3}0.518{col 60}{space 4}-.7744213{col 73}{space 3}  1.53739
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.672612{col 32}{space 2} 1.008558{col 43}{space 1}   -2.65{col 52}{space 3}0.008{col 60}{space 4}-4.649382{col 73}{space 3}-.6958418
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.66894{col 32}{space 2} .0116813{col 43}{space 1} 2967.91{col 52}{space 3}0.000{col 60}{space 4} 34.64605{col 73}{space 3} 34.69184
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    72790{col 38}{space 1}    72790{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25107 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   196,192
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  72789{txt}){col 67}= {res}  49337.37
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9159
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8662
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7220
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    72,790{txt}{col 51}Root MSE{col 67}= {res}    6.4928

{txt}{ralign 84:(Std. err. adjusted for {res:72,790} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.24581{col 32}{space 2} .0766055{col 43}{space 1} -264.29{col 52}{space 3}0.000{col 60}{space 4}-20.39596{col 73}{space 3}-20.09567
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3727477{col 32}{space 2} .0776273{col 43}{space 1}    4.80{col 52}{space 3}0.000{col 60}{space 4} .2205984{col 73}{space 3} .5248969
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7652598{col 32}{space 2}  .589536{col 43}{space 1}    1.30{col 52}{space 3}0.194{col 60}{space 4}-.3902287{col 73}{space 3} 1.920748
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.854073{col 32}{space 2} 1.008355{col 43}{space 1}   -3.82{col 52}{space 3}0.000{col 60}{space 4}-5.830446{col 73}{space 3}  -1.8777
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-13.92969{col 32}{space 2} .0374091{col 43}{space 1} -372.36{col 52}{space 3}0.000{col 60}{space 4}-14.00301{col 73}{space 3}-13.85637
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  41.2619{col 32}{space 2} .0241686{col 43}{space 1} 1707.25{col 52}{space 3}0.000{col 60}{space 4} 41.21453{col 73}{space 3} 41.30927
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    72790{col 38}{space 1}    72790{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 31874 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   116,840
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  58419{txt}){col 67}= {res}  10330.90
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9371
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8743
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4018
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    58,420{txt}{col 51}Root MSE{col 67}= {res}    5.2429

{txt}{ralign 84:(Std. err. adjusted for {res:58,420} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.129319{col 32}{space 2} .0634362{col 43}{space 1}  -96.62{col 52}{space 3}0.000{col 60}{space 4}-6.253655{col 73}{space 3}-6.004984
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .078493{col 32}{space 2} .0719276{col 43}{space 1}    1.09{col 52}{space 3}0.275{col 60}{space 4}-.0624854{col 73}{space 3} .2194714
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.175406{col 32}{space 2}  .693411{col 43}{space 1}    1.70{col 52}{space 3}0.090{col 60}{space 4}-.1836826{col 73}{space 3} 2.534495
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.183993{col 32}{space 2} 1.121981{col 43}{space 1}   -2.84{col 52}{space 3}0.005{col 60}{space 4}-5.383082{col 73}{space 3}-.9849048
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.31333{col 32}{space 2} .0153381{col 43}{space 1} 1780.75{col 52}{space 3}0.000{col 60}{space 4} 27.28327{col 73}{space 3}  27.3434
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    58420{col 38}{space 1}    58420{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26049 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   202,381
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  75232{txt}){col 67}= {res}  44060.65
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8199
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7134
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4223
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,233{txt}{col 51}Root MSE{col 67}= {res}    9.4386

{txt}{ralign 84:(Std. err. adjusted for {res:75,233} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.93163{col 32}{space 2} .0693481{col 43}{space 1} -186.47{col 52}{space 3}0.000{col 60}{space 4}-13.06755{col 73}{space 3}-12.79571
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.9966927{col 32}{space 2}  .078668{col 43}{space 1}  -12.67{col 52}{space 3}0.000{col 60}{space 4}-1.150882{col 73}{space 3}-.8425039
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4159221{col 32}{space 2} .5895171{col 43}{space 1}    0.71{col 52}{space 3}0.480{col 60}{space 4}-.7395287{col 73}{space 3} 1.571373
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.484633{col 32}{space 2} 1.008428{col 43}{space 1}   -2.46{col 52}{space 3}0.014{col 60}{space 4}-4.461147{col 73}{space 3}-.5081179
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.49516{col 32}{space 2} .0116312{col 43}{space 1} 2965.74{col 52}{space 3}0.000{col 60}{space 4} 34.47237{col 73}{space 3} 34.51796
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75233{col 38}{space 1}    75233{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26049 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   202,381
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  75232{txt}){col 67}= {res}  51018.47
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9142
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8634
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7247
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,233{txt}{col 51}Root MSE{col 67}= {res}    6.5159

{txt}{ralign 84:(Std. err. adjusted for {res:75,233} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.32252{col 32}{space 2} .0745873{col 43}{space 1} -272.47{col 52}{space 3}0.000{col 60}{space 4}-20.46871{col 73}{space 3}-20.17633
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2497783{col 32}{space 2} .0758983{col 43}{space 1}    3.29{col 52}{space 3}0.001{col 60}{space 4}  .101018{col 73}{space 3} .3985387
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7953691{col 32}{space 2} .5893154{col 43}{space 1}    1.35{col 52}{space 3}0.177{col 60}{space 4}-.3596865{col 73}{space 3} 1.950425
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.731104{col 32}{space 2} 1.008223{col 43}{space 1}   -3.70{col 52}{space 3}0.000{col 60}{space 4}-5.707216{col 73}{space 3}-1.754991
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.02289{col 32}{space 2} .0369174{col 43}{space 1} -379.85{col 52}{space 3}0.000{col 60}{space 4}-14.09525{col 73}{space 3}-13.95053
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.09276{col 32}{space 2} .0238375{col 43}{space 1} 1723.87{col 52}{space 3}0.000{col 60}{space 4} 41.04604{col 73}{space 3} 41.13949
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75233{col 38}{space 1}    75233{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30573 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   113,278
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  56638{txt}){col 67}= {res}   9822.60
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9377
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8754
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3959
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    56,639{txt}{col 51}Root MSE{col 67}= {res}    5.1952

{txt}{ralign 84:(Std. err. adjusted for {res:56,639} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.122634{col 32}{space 2} .0643905{col 43}{space 1}  -95.09{col 52}{space 3}0.000{col 60}{space 4} -6.24884{col 73}{space 3}-5.996429
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2605497{col 32}{space 2} .0727136{col 43}{space 1}    3.58{col 52}{space 3}0.000{col 60}{space 4} .1180306{col 73}{space 3} .4030687
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.168721{col 32}{space 2} .6934995{col 43}{space 1}    1.69{col 52}{space 3}0.092{col 60}{space 4}-.1905418{col 73}{space 3} 2.527984
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -3.36605{col 32}{space 2} 1.122033{col 43}{space 1}   -3.00{col 52}{space 3}0.003{col 60}{space 4}-5.565241{col 73}{space 3}-1.166859
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 26.94337{col 32}{space 2} .0154358{col 43}{space 1} 1745.51{col 52}{space 3}0.000{col 60}{space 4} 26.91311{col 73}{space 3} 26.97362
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    56639{col 38}{space 1}    56639{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25059 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   195,621
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  72632{txt}){col 67}= {res}  42114.12
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8186
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7115
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4156
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    72,633{txt}{col 51}Root MSE{col 67}= {res}    9.4601

{txt}{ralign 84:(Std. err. adjusted for {res:72,633} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.94376{col 32}{space 2}  .070527{col 43}{space 1} -183.53{col 52}{space 3}0.000{col 60}{space 4}-13.08199{col 73}{space 3}-12.80552
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.7922615{col 32}{space 2} .0798925{col 43}{space 1}   -9.92{col 52}{space 3}0.000{col 60}{space 4}-.9488505{col 73}{space 3}-.6356725
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4280502{col 32}{space 2} .5896573{col 43}{space 1}    0.73{col 52}{space 3}0.468{col 60}{space 4}-.7276761{col 73}{space 3} 1.583777
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.689064{col 32}{space 2} 1.008525{col 43}{space 1}   -2.67{col 52}{space 3}0.008{col 60}{space 4}-4.665769{col 73}{space 3}-.7123582
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.11152{col 32}{space 2} .0117636{col 43}{space 1} 2899.76{col 52}{space 3}0.000{col 60}{space 4} 34.08847{col 73}{space 3} 34.13458
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    72633{col 38}{space 1}    72633{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25059 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   195,621
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  72632{txt}){col 67}= {res}  48863.89
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9144
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8639
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7243
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    72,633{txt}{col 51}Root MSE{col 67}= {res}    6.4983

{txt}{ralign 84:(Std. err. adjusted for {res:72,633} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.36634{col 32}{space 2} .0759138{col 43}{space 1} -268.28{col 52}{space 3}0.000{col 60}{space 4}-20.51513{col 73}{space 3}-20.21755
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4180929{col 32}{space 2} .0771162{col 43}{space 1}    5.42{col 52}{space 3}0.000{col 60}{space 4} .2669453{col 73}{space 3} .5692404
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .8009261{col 32}{space 2} .5894506{col 43}{space 1}    1.36{col 52}{space 3}0.174{col 60}{space 4}-.3543952{col 73}{space 3} 1.956247
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.899418{col 32}{space 2} 1.008316{col 43}{space 1}   -3.87{col 52}{space 3}0.000{col 60}{space 4}-5.875714{col 73}{space 3}-1.923122
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.09942{col 32}{space 2} .0373639{col 43}{space 1} -377.35{col 52}{space 3}0.000{col 60}{space 4}-14.17265{col 73}{space 3}-14.02618
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.76774{col 32}{space 2} .0242819{col 43}{space 1} 1678.93{col 52}{space 3}0.000{col 60}{space 4} 40.72015{col 73}{space 3} 40.81533
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    72633{col 38}{space 1}    72633{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30065 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   108,968
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  54483{txt}){col 67}= {res}   9836.08
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9342
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8684
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4010
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    54,484{txt}{col 51}Root MSE{col 67}= {res}    5.1382

{txt}{ralign 84:(Std. err. adjusted for {res:54,484} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.194908{col 32}{space 2} .0664529{col 43}{space 1}  -93.22{col 52}{space 3}0.000{col 60}{space 4}-6.325156{col 73}{space 3} -6.06466
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3737413{col 32}{space 2} .0743393{col 43}{space 1}    5.03{col 52}{space 3}0.000{col 60}{space 4} .2280358{col 73}{space 3} .5194468
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.240995{col 32}{space 2} .6936947{col 43}{space 1}    1.79{col 52}{space 3}0.074{col 60}{space 4}-.1186521{col 73}{space 3} 2.600642
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.479242{col 32}{space 2} 1.122141{col 43}{space 1}   -3.10{col 52}{space 3}0.002{col 60}{space 4}-5.678646{col 73}{space 3}-1.279838
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 26.20093{col 32}{space 2} .0155653{col 43}{space 1} 1683.29{col 52}{space 3}0.000{col 60}{space 4} 26.17042{col 73}{space 3} 26.23143
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    54484{col 38}{space 1}    54484{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 24230 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   189,131
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  70339{txt}){col 67}= {res}  42122.85
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8128
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7019
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4236
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    70,340{txt}{col 51}Root MSE{col 67}= {res}    9.4372

{txt}{ralign 84:(Std. err. adjusted for {res:70,340} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-13.30853{col 32}{space 2}  .070078{col 43}{space 1} -189.91{col 52}{space 3}0.000{col 60}{space 4}-13.44589{col 73}{space 3}-13.17118
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.5347051{col 32}{space 2} .0797952{col 43}{space 1}   -6.70{col 52}{space 3}0.000{col 60}{space 4}-.6911036{col 73}{space 3}-.3783066
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7928266{col 32}{space 2} .5896041{col 43}{space 1}    1.34{col 52}{space 3}0.179{col 60}{space 4} -.362796{col 73}{space 3} 1.948449
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -2.94662{col 32}{space 2} 1.008518{col 43}{space 1}   -2.92{col 52}{space 3}0.003{col 60}{space 4}-4.923313{col 73}{space 3}-.9699275
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 33.60208{col 32}{space 2} .0118927{col 43}{space 1} 2825.43{col 52}{space 3}0.000{col 60}{space 4} 33.57877{col 73}{space 3} 33.62539
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    70340{col 38}{space 1}    70340{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 24230 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   189,131
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  70339{txt}){col 67}= {res}  50612.25
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9157
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8657
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7404
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    70,340{txt}{col 51}Root MSE{col 67}= {res}    6.3339

{txt}{ralign 84:(Std. err. adjusted for {res:70,340} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}  -20.864{col 32}{space 2}  .073893{col 43}{space 1} -282.35{col 52}{space 3}0.000{col 60}{space 4}-21.00883{col 73}{space 3}-20.71917
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7437423{col 32}{space 2} .0765023{col 43}{space 1}    9.72{col 52}{space 3}0.000{col 60}{space 4}  .593798{col 73}{space 3} .8936867
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.165328{col 32}{space 2}  .589373{col 43}{space 1}    1.98{col 52}{space 3}0.048{col 60}{space 4}  .010158{col 73}{space 3} 2.320497
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-4.225068{col 32}{space 2}  1.00827{col 43}{space 1}   -4.19{col 52}{space 3}0.000{col 60}{space 4}-6.201275{col 73}{space 3} -2.24886
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.36592{col 32}{space 2} .0363649{col 43}{space 1} -395.05{col 52}{space 3}0.000{col 60}{space 4} -14.4372{col 73}{space 3}-14.29465
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.35107{col 32}{space 2} .0237533{col 43}{space 1} 1698.76{col 52}{space 3}0.000{col 60}{space 4} 40.30451{col 73}{space 3} 40.39763
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    70340{col 38}{space 1}    70340{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 27897 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   102,038
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  51018{txt}){col 67}= {res}   8941.81
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9216
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8433
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4020
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    51,019{txt}{col 51}Root MSE{col 67}= {res}    5.5300

{txt}{ralign 84:(Std. err. adjusted for {res:51,019} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.578984{col 32}{space 2} .0706424{col 43}{space 1}  -93.13{col 52}{space 3}0.000{col 60}{space 4}-6.717444{col 73}{space 3}-6.440524
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2485705{col 32}{space 2} .0804789{col 43}{space 1}    3.09{col 52}{space 3}0.002{col 60}{space 4} .0908311{col 73}{space 3} .4063099
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  1.62507{col 32}{space 2} .6941099{col 43}{space 1}    2.34{col 52}{space 3}0.019{col 60}{space 4} .2646078{col 73}{space 3} 2.985533
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.354071{col 32}{space 2} 1.122566{col 43}{space 1}   -2.99{col 52}{space 3}0.003{col 60}{space 4}-5.554312{col 73}{space 3} -1.15383
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 30.27065{col 32}{space 2} .0173117{col 43}{space 1} 1748.56{col 52}{space 3}0.000{col 60}{space 4} 30.23672{col 73}{space 3} 30.30459
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    51019{col 38}{space 1}    51019{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 23052 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   176,672
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  65702{txt}){col 67}= {res}  41704.67
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.7846
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6571
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4312
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    65,703{txt}{col 51}Root MSE{col 67}= {res}    9.8688

{txt}{ralign 84:(Std. err. adjusted for {res:65,703} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-13.90367{col 32}{space 2} .0744347{col 43}{space 1} -186.79{col 52}{space 3}0.000{col 60}{space 4}-14.04956{col 73}{space 3}-13.75778
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.8759918{col 32}{space 2} .0848933{col 43}{space 1}  -10.32{col 52}{space 3}0.000{col 60}{space 4}-1.042383{col 73}{space 3} -.709601
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.387963{col 32}{space 2} .5901385{col 43}{space 1}    2.35{col 52}{space 3}0.019{col 60}{space 4} .2312913{col 73}{space 3} 2.544634
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.605334{col 32}{space 2} 1.008935{col 43}{space 1}   -2.58{col 52}{space 3}0.010{col 60}{space 4}-4.582847{col 73}{space 3}-.6278203
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 37.93869{col 32}{space 2}  .012708{col 43}{space 1} 2985.42{col 52}{space 3}0.000{col 60}{space 4} 37.91379{col 73}{space 3}  37.9636
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    65703{col 38}{space 1}    65703{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 23052 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   176,672
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  65702{txt}){col 67}= {res}  51220.05
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9037
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8467
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7458
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    65,703{txt}{col 51}Root MSE{col 67}= {res}    6.5981

{txt}{ralign 84:(Std. err. adjusted for {res:65,703} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-21.83119{col 32}{space 2} .0791072{col 43}{space 1} -275.97{col 52}{space 3}0.000{col 60}{space 4}-21.98624{col 73}{space 3}-21.67614
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4393754{col 32}{space 2} .0813613{col 43}{space 1}    5.40{col 52}{space 3}0.000{col 60}{space 4} .2799072{col 73}{space 3} .5988437
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.776704{col 32}{space 2} .5898578{col 43}{space 1}    3.01{col 52}{space 3}0.003{col 60}{space 4} .6205822{col 73}{space 3} 2.932825
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.920701{col 32}{space 2} 1.008652{col 43}{space 1}   -3.89{col 52}{space 3}0.000{col 60}{space 4}-5.897659{col 73}{space 3}-1.943742
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-15.07756{col 32}{space 2} .0400996{col 43}{space 1} -376.00{col 52}{space 3}0.000{col 60}{space 4}-15.15615{col 73}{space 3}-14.99896
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 45.03432{col 32}{space 2} .0253901{col 43}{space 1} 1773.70{col 52}{space 3}0.000{col 60}{space 4} 44.98456{col 73}{space 3} 45.08409
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    65703{col 38}{space 1}    65703{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 31667 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   115,588
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  57793{txt}){col 67}= {res}  10104.32
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9384
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8768
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3993
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    57,794{txt}{col 51}Root MSE{col 67}= {res}    5.1939

{txt}{ralign 84:(Std. err. adjusted for {res:57,794} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-5.993812{col 32}{space 2} .0627731{col 43}{space 1}  -95.48{col 52}{space 3}0.000{col 60}{space 4}-6.116848{col 73}{space 3}-5.870777
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .008874{col 32}{space 2} .0713429{col 43}{space 1}    0.12{col 52}{space 3}0.901{col 60}{space 4}-.1309585{col 73}{space 3} .1487065
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.039899{col 32}{space 2} .6933508{col 43}{space 1}    1.50{col 52}{space 3}0.134{col 60}{space 4} -.319072{col 73}{space 3}  2.39887
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.114374{col 32}{space 2} 1.121944{col 43}{space 1}   -2.78{col 52}{space 3}0.006{col 60}{space 4}-5.313391{col 73}{space 3}-.9153579
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.24864{col 32}{space 2} .0152768{col 43}{space 1} 1783.66{col 52}{space 3}0.000{col 60}{space 4}  27.2187{col 73}{space 3} 27.27858
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    57794{col 38}{space 1}    57794{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25693 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,353
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  74450{txt}){col 67}= {res}  43903.10
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8204
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7142
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4211
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,451{txt}{col 51}Root MSE{col 67}= {res}    9.4435

{txt}{ralign 84:(Std. err. adjusted for {res:74,451} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.77273{col 32}{space 2} .0687475{col 43}{space 1} -185.79{col 52}{space 3}0.000{col 60}{space 4}-12.90748{col 73}{space 3}-12.63799
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.185987{col 32}{space 2} .0782014{col 43}{space 1}  -15.17{col 52}{space 3}0.000{col 60}{space 4}-1.339262{col 73}{space 3}-1.032713
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2570283{col 32}{space 2} .5894469{col 43}{space 1}    0.44{col 52}{space 3}0.663{col 60}{space 4}-.8982851{col 73}{space 3} 1.412342
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.295338{col 32}{space 2} 1.008392{col 43}{space 1}   -2.28{col 52}{space 3}0.023{col 60}{space 4}-4.271782{col 73}{space 3}-.3188937
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.49153{col 32}{space 2} .0116186{col 43}{space 1} 2968.65{col 52}{space 3}0.000{col 60}{space 4} 34.46876{col 73}{space 3} 34.51431
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74451{col 38}{space 1}    74451{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25693 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   200,353
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  74450{txt}){col 67}= {res}  51278.37
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9157
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8658
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7282
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,451{txt}{col 51}Root MSE{col 67}= {res}    6.4705

{txt}{ralign 84:(Std. err. adjusted for {res:74,451} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.20795{col 32}{space 2} .0739446{col 43}{space 1} -273.29{col 52}{space 3}0.000{col 60}{space 4}-20.35288{col 73}{space 3}-20.06302
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0700759{col 32}{space 2} .0753547{col 43}{space 1}    0.93{col 52}{space 3}0.352{col 60}{space 4} -.077619{col 73}{space 3} .2177708
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .6323748{col 32}{space 2} .5892412{col 43}{space 1}    1.07{col 52}{space 3}0.283{col 60}{space 4}-.5225355{col 73}{space 3} 1.787285
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.551401{col 32}{space 2} 1.008182{col 43}{space 1}   -3.52{col 52}{space 3}0.000{col 60}{space 4}-5.527435{col 73}{space 3}-1.575368
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.11974{col 32}{space 2} .0368069{col 43}{space 1} -383.62{col 52}{space 3}0.000{col 60}{space 4}-14.19188{col 73}{space 3} -14.0476
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.13008{col 32}{space 2} .0237773{col 43}{space 1} 1729.80{col 52}{space 3}0.000{col 60}{space 4} 41.08347{col 73}{space 3} 41.17668
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74451{col 38}{space 1}    74451{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30632 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   110,118
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  55058{txt}){col 67}= {res}  10085.93
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9370
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8740
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4110
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    55,059{txt}{col 51}Root MSE{col 67}= {res}    5.1803

{txt}{ralign 84:(Std. err. adjusted for {res:55,059} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.177738{col 32}{space 2} .0640535{col 43}{space 1}  -96.45{col 52}{space 3}0.000{col 60}{space 4}-6.303283{col 73}{space 3}-6.052193
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .087667{col 32}{space 2} .0728209{col 43}{space 1}    1.20{col 52}{space 3}0.229{col 60}{space 4}-.0550624{col 73}{space 3} .2303965
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.223825{col 32}{space 2} .6934688{col 43}{space 1}    1.76{col 52}{space 3}0.078{col 60}{space 4}-.1353789{col 73}{space 3} 2.583029
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.193167{col 32}{space 2} 1.122041{col 43}{space 1}   -2.85{col 52}{space 3}0.004{col 60}{space 4}-5.392375{col 73}{space 3}-.9939597
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 26.97958{col 32}{space 2} .0156106{col 43}{space 1} 1728.28{col 52}{space 3}0.000{col 60}{space 4} 26.94899{col 73}{space 3} 27.01018
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    55059{col 38}{space 1}    55059{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25000 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   191,103
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  71101{txt}){col 67}= {res}  42000.74
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8202
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7136
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4253
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    71,102{txt}{col 51}Root MSE{col 67}= {res}    9.4026

{txt}{ralign 84:(Std. err. adjusted for {res:71,102} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.88145{col 32}{space 2} .0696502{col 43}{space 1} -184.94{col 52}{space 3}0.000{col 60}{space 4}-13.01796{col 73}{space 3}-12.74494
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.105568{col 32}{space 2} .0795145{col 43}{space 1}  -13.90{col 52}{space 3}0.000{col 60}{space 4}-1.261417{col 73}{space 3}-.9497201
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3657432{col 32}{space 2} .5895533{col 43}{space 1}    0.62{col 52}{space 3}0.535{col 60}{space 4}-.7897797{col 73}{space 3} 1.521266
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.375757{col 32}{space 2} 1.008496{col 43}{space 1}   -2.36{col 52}{space 3}0.018{col 60}{space 4}-4.352406{col 73}{space 3}-.3991084
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  34.1425{col 32}{space 2} .0119207{col 43}{space 1} 2864.14{col 52}{space 3}0.000{col 60}{space 4} 34.11914{col 73}{space 3} 34.16586
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    71102{col 38}{space 1}    71102{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25000 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   191,103
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  71101{txt}){col 67}= {res}  48075.19
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9144
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8637
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7265
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    71,102{txt}{col 51}Root MSE{col 67}= {res}    6.4862

{txt}{ralign 84:(Std. err. adjusted for {res:71,102} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.24712{col 32}{space 2} .0748427{col 43}{space 1} -270.53{col 52}{space 3}0.000{col 60}{space 4}-20.39381{col 73}{space 3}-20.10043
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .149976{col 32}{space 2} .0765747{col 43}{space 1}    1.96{col 52}{space 3}0.050{col 60}{space 4}-.0001102{col 73}{space 3} .3000621
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7386237{col 32}{space 2} .5893397{col 43}{space 1}    1.25{col 52}{space 3}0.210{col 60}{space 4}-.4164806{col 73}{space 3} 1.893728
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.631301{col 32}{space 2} 1.008276{col 43}{space 1}   -3.60{col 52}{space 3}0.000{col 60}{space 4}-5.607519{col 73}{space 3}-1.655084
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-13.98559{col 32}{space 2} .0378008{col 43}{space 1} -369.98{col 52}{space 3}0.000{col 60}{space 4}-14.05968{col 73}{space 3} -13.9115
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.71271{col 32}{space 2} .0244486{col 43}{space 1} 1665.24{col 52}{space 3}0.000{col 60}{space 4} 40.66479{col 73}{space 3} 40.76063
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    71102{col 38}{space 1}    71102{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25779 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   102,378
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  51188{txt}){col 67}= {res}   7750.25
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9380
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8759
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3581
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    51,189{txt}{col 51}Root MSE{col 67}= {res}    5.3362

{txt}{ralign 84:(Std. err. adjusted for {res:51,189} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-4.910357{col 32}{space 2} .0723942{col 43}{space 1}  -67.83{col 52}{space 3}0.000{col 60}{space 4} -5.05225{col 73}{space 3}-4.768464
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.9997615{col 32}{space 2} .0810604{col 43}{space 1}  -12.33{col 52}{space 3}0.000{col 60}{space 4}-1.158641{col 73}{space 3}-.8408823
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.0435562{col 32}{space 2} .6942903{col 43}{space 1}   -0.06{col 52}{space 3}0.950{col 60}{space 4}-1.404372{col 73}{space 3}  1.31726
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.105739{col 32}{space 2} 1.122608{col 43}{space 1}   -1.88{col 52}{space 3}0.061{col 60}{space 4}-4.306062{col 73}{space 3} .0945842
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 26.94944{col 32}{space 2} .0166773{col 43}{space 1} 1615.93{col 52}{space 3}0.000{col 60}{space 4} 26.91676{col 73}{space 3} 26.98213
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    51189{col 38}{space 1}    51189{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 22427 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   175,678
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  65289{txt}){col 67}= {res}  34289.75
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8268
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7244
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4008
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    65,290{txt}{col 51}Root MSE{col 67}= {res}    9.3631

{txt}{ralign 84:(Std. err. adjusted for {res:65,290} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-11.38196{col 32}{space 2}  .078825{col 43}{space 1} -144.40{col 52}{space 3}0.000{col 60}{space 4}-11.53646{col 73}{space 3}-11.22746
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-2.035027{col 32}{space 2} .0881611{col 43}{space 1}  -23.08{col 52}{space 3}0.000{col 60}{space 4}-2.207823{col 73}{space 3}-1.862231
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.133748{col 32}{space 2} .5907084{col 43}{space 1}   -1.92{col 52}{space 3}0.055{col 60}{space 4}-2.291537{col 73}{space 3} .0240402
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-1.446298{col 32}{space 2} 1.009216{col 43}{space 1}   -1.43{col 52}{space 3}0.152{col 60}{space 4}-3.424361{col 73}{space 3} .5317646
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 33.74615{col 32}{space 2} .0126178{col 43}{space 1} 2674.48{col 52}{space 3}0.000{col 60}{space 4} 33.72142{col 73}{space 3} 33.77088
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    65290{col 38}{space 1}    65290{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 22427 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   175,678
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  65289{txt}){col 67}= {res}  38856.06
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9116
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8593
{txt}{col 51}Within R-sq.{col 67}= {res}    0.6941
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    65,290{txt}{col 51}Root MSE{col 67}= {res}    6.6902

{txt}{ralign 84:(Std. err. adjusted for {res:65,290} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-18.59848{col 32}{space 2} .0855152{col 43}{space 1} -217.49{col 52}{space 3}0.000{col 60}{space 4}-18.76609{col 73}{space 3}-18.43087
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.7965189{col 32}{space 2} .0858714{col 43}{space 1}   -9.28{col 52}{space 3}0.000{col 60}{space 4}-.9648269{col 73}{space 3} -.628211
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.6597322{col 32}{space 2}   .59053{col 43}{space 1}   -1.12{col 52}{space 3}0.264{col 60}{space 4}-1.817171{col 73}{space 3} .4977069
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.684806{col 32}{space 2} 1.009027{col 43}{space 1}   -2.66{col 52}{space 3}0.008{col 60}{space 4}-4.662499{col 73}{space 3}-.7071141
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-13.48502{col 32}{space 2} .0414641{col 43}{space 1} -325.22{col 52}{space 3}0.000{col 60}{space 4}-13.56629{col 73}{space 3}-13.40375
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.12914{col 32}{space 2} .0266204{col 43}{space 1} 1507.46{col 52}{space 3}0.000{col 60}{space 4} 40.07696{col 73}{space 3} 40.18131
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    65290{col 38}{space 1}    65290{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 31376 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   117,264
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  58631{txt}){col 67}= {res}  10423.23
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4033
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    58,632{txt}{col 51}Root MSE{col 67}= {res}    5.2379

{txt}{ralign 84:(Std. err. adjusted for {res:58,632} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.121899{col 32}{space 2}  .062844{col 43}{space 1}  -97.41{col 52}{space 3}0.000{col 60}{space 4}-6.245074{col 73}{space 3}-5.998725
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0487604{col 32}{space 2} .0714108{col 43}{space 1}    0.68{col 52}{space 3}0.495{col 60}{space 4}-.0912052{col 73}{space 3} .1887259
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.167986{col 32}{space 2}  .693357{col 43}{space 1}    1.68{col 52}{space 3}0.092{col 60}{space 4}-.1909967{col 73}{space 3} 2.526969
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.154261{col 32}{space 2} 1.121948{col 43}{space 1}   -2.81{col 52}{space 3}0.005{col 60}{space 4}-5.353284{col 73}{space 3}-.9552372
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.45703{col 32}{space 2} .0152959{col 43}{space 1} 1795.06{col 52}{space 3}0.000{col 60}{space 4} 27.42705{col 73}{space 3} 27.48701
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    58632{col 38}{space 1}    58632{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26018 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   202,042
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  74968{txt}){col 67}= {res}  44205.95
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8189
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7120
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4220
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,969{txt}{col 51}Root MSE{col 67}= {res}    9.4627

{txt}{ralign 84:(Std. err. adjusted for {res:74,969} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.92846{col 32}{space 2} .0686972{col 43}{space 1} -188.19{col 52}{space 3}0.000{col 60}{space 4} -13.0631{col 73}{space 3}-12.79381
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.034494{col 32}{space 2} .0781428{col 43}{space 1}  -13.24{col 52}{space 3}0.000{col 60}{space 4}-1.187654{col 73}{space 3}-.8813348
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4127518{col 32}{space 2} .5894409{col 43}{space 1}    0.70{col 52}{space 3}0.484{col 60}{space 4}-.7425498{col 73}{space 3} 1.568053
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.446831{col 32}{space 2} 1.008387{col 43}{space 1}   -2.43{col 52}{space 3}0.015{col 60}{space 4}-4.423266{col 73}{space 3}-.4703962
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.72107{col 32}{space 2} .0116395{col 43}{space 1} 2983.03{col 52}{space 3}0.000{col 60}{space 4} 34.69825{col 73}{space 3} 34.74388
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74969{col 38}{space 1}    74969{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26018 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   202,042
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  74968{txt}){col 67}= {res}  51393.86
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9144
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8639
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7270
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    74,969{txt}{col 51}Root MSE{col 67}= {res}    6.5039

{txt}{ralign 84:(Std. err. adjusted for {res:74,969} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.37022{col 32}{space 2} .0739571{col 43}{space 1} -275.43{col 52}{space 3}0.000{col 60}{space 4}-20.51517{col 73}{space 3}-20.22526
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1949667{col 32}{space 2} .0753557{col 43}{space 1}    2.59{col 52}{space 3}0.010{col 60}{space 4} .0472699{col 73}{space 3} .3426636
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7945871{col 32}{space 2} .5892422{col 43}{space 1}    1.35{col 52}{space 3}0.178{col 60}{space 4} -.360325{col 73}{space 3} 1.949499
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.676292{col 32}{space 2} 1.008182{col 43}{space 1}   -3.65{col 52}{space 3}0.000{col 60}{space 4}-5.652325{col 73}{space 3}-1.700259
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.11985{col 32}{space 2} .0368294{col 43}{space 1} -383.39{col 52}{space 3}0.000{col 60}{space 4}-14.19203{col 73}{space 3}-14.04766
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.38088{col 32}{space 2}  .023858{col 43}{space 1} 1734.46{col 52}{space 3}0.000{col 60}{space 4} 41.33412{col 73}{space 3} 41.42764
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    74969{col 38}{space 1}    74969{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30602 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   113,424
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  56711{txt}){col 67}= {res}  10161.17
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9355
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8709
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4056
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    56,712{txt}{col 51}Root MSE{col 67}= {res}    5.2593

{txt}{ralign 84:(Std. err. adjusted for {res:56,712} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.026247{col 32}{space 2} .0636721{col 43}{space 1}  -94.64{col 52}{space 3}0.000{col 60}{space 4}-6.151045{col 73}{space 3} -5.90145
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.1706738{col 32}{space 2} .0726033{col 43}{space 1}   -2.35{col 52}{space 3}0.019{col 60}{space 4}-.3129767{col 73}{space 3}-.0283709
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.072334{col 32}{space 2} .6934331{col 43}{space 1}    1.55{col 52}{space 3}0.122{col 60}{space 4}-.2867989{col 73}{space 3} 2.431467
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.934827{col 32}{space 2} 1.122026{col 43}{space 1}   -2.62{col 52}{space 3}0.009{col 60}{space 4}-5.134004{col 73}{space 3}-.7356496
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 28.13311{col 32}{space 2} .0156161{col 43}{space 1} 1801.54{col 52}{space 3}0.000{col 60}{space 4}  28.1025{col 73}{space 3} 28.16372
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    56712{col 38}{space 1}    56712{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 24973 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   196,065
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  72784{txt}){col 67}= {res}  44943.52
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8118
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7007
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4268
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    72,785{txt}{col 51}Root MSE{col 67}= {res}    9.5544

{txt}{ralign 84:(Std. err. adjusted for {res:72,785} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-13.02892{col 32}{space 2} .0702415{col 43}{space 1} -185.49{col 52}{space 3}0.000{col 60}{space 4}-13.16659{col 73}{space 3}-12.89124
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.276628{col 32}{space 2} .0796859{col 43}{space 1}  -16.02{col 52}{space 3}0.000{col 60}{space 4}-1.432812{col 73}{space 3}-1.120444
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .5132099{col 32}{space 2} .5896232{col 43}{space 1}    0.87{col 52}{space 3}0.384{col 60}{space 4}-.6424496{col 73}{space 3} 1.668869
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.204697{col 32}{space 2} 1.008509{col 43}{space 1}   -2.19{col 52}{space 3}0.029{col 60}{space 4}-4.181371{col 73}{space 3}-.2280238
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 35.53552{col 32}{space 2} .0117745{col 43}{space 1} 3018.01{col 52}{space 3}0.000{col 60}{space 4} 35.51244{col 73}{space 3}  35.5586
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    72785{col 38}{space 1}    72785{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 24973 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   196,065
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  72784{txt}){col 67}= {res}  53603.44
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9139
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8631
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7378
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    72,785{txt}{col 51}Root MSE{col 67}= {res}    6.4624

{txt}{ralign 84:(Std. err. adjusted for {res:72,785} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.63403{col 32}{space 2} .0754374{col 43}{space 1} -273.53{col 52}{space 3}0.000{col 60}{space 4}-20.78188{col 73}{space 3}-20.48617
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.0134015{col 32}{space 2} .0766841{col 43}{space 1}   -0.17{col 52}{space 3}0.861{col 60}{space 4}-.1637021{col 73}{space 3} .1368991
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .8960195{col 32}{space 2} .5893967{col 43}{space 1}    1.52{col 52}{space 3}0.128{col 60}{space 4}-.2591961{col 73}{space 3} 2.051235
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.467924{col 32}{space 2} 1.008283{col 43}{space 1}   -3.44{col 52}{space 3}0.001{col 60}{space 4}-5.444155{col 73}{space 3}-1.491692
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2} -14.4446{col 32}{space 2} .0371787{col 43}{space 1} -388.52{col 52}{space 3}0.000{col 60}{space 4}-14.51747{col 73}{space 3}-14.37173
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 42.33781{col 32}{space 2}  .023918{col 43}{space 1} 1770.12{col 52}{space 3}0.000{col 60}{space 4} 42.29093{col 73}{space 3} 42.38469
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    72785{col 38}{space 1}    72785{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30993 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   115,078
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  57538{txt}){col 67}= {res}  10212.26
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9379
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8757
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4034
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    57,539{txt}{col 51}Root MSE{col 67}= {res}    5.2104

{txt}{ralign 84:(Std. err. adjusted for {res:57,539} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.076334{col 32}{space 2} .0635543{col 43}{space 1}  -95.61{col 52}{space 3}0.000{col 60}{space 4}  -6.2009{col 73}{space 3}-5.951767
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0256317{col 32}{space 2} .0721021{col 43}{space 1}    0.36{col 52}{space 3}0.722{col 60}{space 4}-.1156888{col 73}{space 3} .1669522
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  1.12242{col 32}{space 2}  .693422{col 43}{space 1}    1.62{col 52}{space 3}0.106{col 60}{space 4}-.2366906{col 73}{space 3} 2.481531
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.131132{col 32}{space 2} 1.121993{col 43}{space 1}   -2.79{col 52}{space 3}0.005{col 60}{space 4}-5.330244{col 73}{space 3}-.9320199
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.14779{col 32}{space 2} .0153593{col 43}{space 1} 1767.51{col 52}{space 3}0.000{col 60}{space 4} 27.11768{col 73}{space 3} 27.17789
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    57539{col 38}{space 1}    57539{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25149 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   199,267
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  73916{txt}){col 67}= {res}  43896.66
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8233
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7190
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4252
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    73,917{txt}{col 51}Root MSE{col 67}= {res}    9.2945

{txt}{ralign 84:(Std. err. adjusted for {res:73,917} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.70234{col 32}{space 2} .0687575{col 43}{space 1} -184.74{col 52}{space 3}0.000{col 60}{space 4} -12.8371{col 73}{space 3}-12.56757
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.137694{col 32}{space 2}  .078037{col 43}{space 1}  -14.58{col 52}{space 3}0.000{col 60}{space 4}-1.290646{col 73}{space 3}-.9847415
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1866318{col 32}{space 2} .5894481{col 43}{space 1}    0.32{col 52}{space 3}0.752{col 60}{space 4}-.9686842{col 73}{space 3} 1.341948
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.343632{col 32}{space 2} 1.008379{col 43}{space 1}   -2.32{col 52}{space 3}0.020{col 60}{space 4}-4.320051{col 73}{space 3} -.367212
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.21967{col 32}{space 2}  .011526{col 43}{space 1} 2968.92{col 52}{space 3}0.000{col 60}{space 4} 34.19708{col 73}{space 3} 34.24227
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    73917{col 38}{space 1}    73917{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 25149 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   199,267
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  73916{txt}){col 67}= {res}  50640.81
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9155
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8657
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7253
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    73,917{txt}{col 51}Root MSE{col 67}= {res}    6.4249

{txt}{ralign 84:(Std. err. adjusted for {res:73,917} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-19.97037{col 32}{space 2} .0737581{col 43}{space 1} -270.75{col 52}{space 3}0.000{col 60}{space 4}-20.11494{col 73}{space 3}-19.82581
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1061209{col 32}{space 2} .0753219{col 43}{space 1}    1.41{col 52}{space 3}0.159{col 60}{space 4}-.0415098{col 73}{space 3} .2537515
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .5622108{col 32}{space 2} .5892475{col 43}{space 1}    0.95{col 52}{space 3}0.340{col 60}{space 4}-.5927121{col 73}{space 3} 1.717134
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.587446{col 32}{space 2}  1.00818{col 43}{space 1}   -3.56{col 52}{space 3}0.000{col 60}{space 4}-5.563475{col 73}{space 3}-1.611417
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-13.78491{col 32}{space 2} .0365998{col 43}{space 1} -376.64{col 52}{space 3}0.000{col 60}{space 4}-13.85664{col 73}{space 3}-13.71317
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.69394{col 32}{space 2} .0235444{col 43}{space 1} 1728.39{col 52}{space 3}0.000{col 60}{space 4} 40.64779{col 73}{space 3} 40.74009
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    73917{col 38}{space 1}    73917{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 31922 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   117,434
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  58716{txt}){col 67}= {res}  10452.01
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9375
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8750
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4035
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    58,717{txt}{col 51}Root MSE{col 67}= {res}    5.2107

{txt}{ralign 84:(Std. err. adjusted for {res:58,717} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.047516{col 32}{space 2} .0627116{col 43}{space 1}  -96.43{col 52}{space 3}0.000{col 60}{space 4}-6.170431{col 73}{space 3}-5.924601
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.0191103{col 32}{space 2} .0712011{col 43}{space 1}   -0.27{col 52}{space 3}0.788{col 60}{space 4}-.1586648{col 73}{space 3} .1204441
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.093603{col 32}{space 2} .6933449{col 43}{space 1}    1.58{col 52}{space 3}0.115{col 60}{space 4}-.2653565{col 73}{space 3} 2.452562
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -3.08639{col 32}{space 2} 1.121935{col 43}{space 1}   -2.75{col 52}{space 3}0.006{col 60}{space 4}-5.285387{col 73}{space 3}-.8873928
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.32338{col 32}{space 2} .0152054{col 43}{space 1} 1796.96{col 52}{space 3}0.000{col 60}{space 4} 27.29357{col 73}{space 3} 27.35318
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    58717{col 38}{space 1}    58717{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26048 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   203,242
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  75511{txt}){col 67}= {res}  44574.67
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8196
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7130
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4224
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,512{txt}{col 51}Root MSE{col 67}= {res}    9.4385

{txt}{ralign 84:(Std. err. adjusted for {res:75,512} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.87115{col 32}{space 2} .0687543{col 43}{space 1} -187.21{col 52}{space 3}0.000{col 60}{space 4}-13.00591{col 73}{space 3}-12.73639
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.087427{col 32}{space 2} .0780724{col 43}{space 1}  -13.93{col 52}{space 3}0.000{col 60}{space 4}-1.240448{col 73}{space 3} -.934405
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3554448{col 32}{space 2} .5894475{col 43}{space 1}    0.60{col 52}{space 3}0.547{col 60}{space 4}-.7998696{col 73}{space 3} 1.510759
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.393899{col 32}{space 2} 1.008382{col 43}{space 1}   -2.37{col 52}{space 3}0.018{col 60}{space 4}-4.370323{col 73}{space 3}-.4174751
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.52495{col 32}{space 2} .0115563{col 43}{space 1} 2987.55{col 52}{space 3}0.000{col 60}{space 4}  34.5023{col 73}{space 3}  34.5476
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75512{col 38}{space 1}    75512{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26048 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   203,242
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  75511{txt}){col 67}= {res}  51731.77
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9147
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8643
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7270
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,512{txt}{col 51}Root MSE{col 67}= {res}    6.4890

{txt}{ralign 84:(Std. err. adjusted for {res:75,512} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.28063{col 32}{space 2} .0739548{col 43}{space 1} -274.23{col 52}{space 3}0.000{col 60}{space 4}-20.42558{col 73}{space 3}-20.13567
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .1465083{col 32}{space 2} .0752743{col 43}{space 1}    1.95{col 52}{space 3}0.052{col 60}{space 4} -.001029{col 73}{space 3} .2940455
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7301573{col 32}{space 2} .5892429{col 43}{space 1}    1.24{col 52}{space 3}0.215{col 60}{space 4}-.4247562{col 73}{space 3} 1.885071
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.627834{col 32}{space 2} 1.008176{col 43}{space 1}   -3.60{col 52}{space 3}0.000{col 60}{space 4}-5.603854{col 73}{space 3}-1.651813
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.06952{col 32}{space 2} .0366718{col 43}{space 1} -383.66{col 52}{space 3}0.000{col 60}{space 4} -14.1414{col 73}{space 3}-13.99765
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.14889{col 32}{space 2} .0237017{col 43}{space 1} 1736.11{col 52}{space 3}0.000{col 60}{space 4} 41.10244{col 73}{space 3} 41.19535
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75512{col 38}{space 1}    75512{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 30604 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   104,826
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  52412{txt}){col 67}= {res}   8993.89
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9388
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8776
{txt}{col 51}Within R-sq.{col 67}= {res}    0.3982
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    52,413{txt}{col 51}Root MSE{col 67}= {res}    5.3467

{txt}{ralign 84:(Std. err. adjusted for {res:52,413} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.450834{col 32}{space 2} .0668026{col 43}{space 1}  -96.57{col 52}{space 3}0.000{col 60}{space 4}-6.581768{col 73}{space 3}  -6.3199
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4523373{col 32}{space 2} .0762863{col 43}{space 1}    5.93{col 52}{space 3}0.000{col 60}{space 4} .3028154{col 73}{space 3} .6018592
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.496921{col 32}{space 2}  .693729{col 43}{space 1}    2.16{col 52}{space 3}0.031{col 60}{space 4} .1372054{col 73}{space 3} 2.856636
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.557838{col 32}{space 2} 1.122272{col 43}{space 1}   -3.17{col 52}{space 3}0.002{col 60}{space 4}-5.757502{col 73}{space 3}-1.358173
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.29014{col 32}{space 2} .0165138{col 43}{space 1} 1652.56{col 52}{space 3}0.000{col 60}{space 4} 27.25777{col 73}{space 3} 27.32251
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    52413{col 38}{space 1}    52413{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 24022 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   183,670
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  68530{txt}){col 67}= {res}  37492.17
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8392
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7435
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4316
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    68,531{txt}{col 51}Root MSE{col 67}= {res}    9.0088

{txt}{ralign 84:(Std. err. adjusted for {res:68,531} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}  -12.796{col 32}{space 2} .0732466{col 43}{space 1} -174.70{col 52}{space 3}0.000{col 60}{space 4}-12.93956{col 73}{space 3}-12.65243
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-.6713108{col 32}{space 2} .0830313{col 43}{space 1}   -8.09{col 52}{space 3}0.000{col 60}{space 4} -.834052{col 73}{space 3}-.5085697
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2802908{col 32}{space 2} .5899894{col 43}{space 1}    0.48{col 52}{space 3}0.635{col 60}{space 4}-.8760876{col 73}{space 3} 1.436669
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.810015{col 32}{space 2}  1.00878{col 43}{space 1}   -2.79{col 52}{space 3}0.005{col 60}{space 4}-4.787221{col 73}{space 3} -.832808
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  34.0057{col 32}{space 2} .0122816{col 43}{space 1} 2768.84{col 52}{space 3}0.000{col 60}{space 4} 33.98163{col 73}{space 3} 34.02977
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    68531{col 38}{space 1}    68531{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 24022 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   183,670
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  68530{txt}){col 67}= {res}  44470.71
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9185
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8700
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7121
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    68,531{txt}{col 51}Root MSE{col 67}= {res}    6.4122

{txt}{ralign 84:(Std. err. adjusted for {res:68,531} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-19.66007{col 32}{space 2} .0789605{col 43}{space 1} -248.99{col 52}{space 3}0.000{col 60}{space 4}-19.81484{col 73}{space 3}-19.50531
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .5912568{col 32}{space 2}  .080532{col 43}{space 1}    7.34{col 52}{space 3}0.000{col 60}{space 4} .4334141{col 73}{space 3} .7490995
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .6406406{col 32}{space 2} .5898113{col 43}{space 1}    1.09{col 52}{space 3}0.277{col 60}{space 4}-.5153887{col 73}{space 3}  1.79667
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-4.072582{col 32}{space 2} 1.008585{col 43}{space 1}   -4.04{col 52}{space 3}0.000{col 60}{space 4}-6.049408{col 73}{space 3}-2.095757
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-13.00745{col 32}{space 2} .0373018{col 43}{space 1} -348.71{col 52}{space 3}0.000{col 60}{space 4}-13.08057{col 73}{space 3}-12.93434
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 40.07552{col 32}{space 2} .0241001{col 43}{space 1} 1662.88{col 52}{space 3}0.000{col 60}{space 4} 40.02829{col 73}{space 3} 40.12276
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    68531{col 38}{space 1}    68531{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 32067 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,204
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59101{txt}){col 67}= {res}  10537.23
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4037
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,102{txt}{col 51}Root MSE{col 67}= {res}    5.2221

{txt}{ralign 84:(Std. err. adjusted for {res:59,102} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.080861{col 32}{space 2} .0628739{col 43}{space 1}  -96.72{col 52}{space 3}0.000{col 60}{space 4}-6.204094{col 73}{space 3}-5.957628
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0074079{col 32}{space 2} .0712919{col 43}{space 1}    0.10{col 52}{space 3}0.917{col 60}{space 4}-.1323246{col 73}{space 3} .1471404
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.126948{col 32}{space 2} .6933595{col 43}{space 1}    1.63{col 52}{space 3}0.104{col 60}{space 4}-.2320395{col 73}{space 3} 2.485936
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.112908{col 32}{space 2}  1.12194{col 43}{space 1}   -2.77{col 52}{space 3}0.006{col 60}{space 4}-5.311916{col 73}{space 3}-.9139004
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.39883{col 32}{space 2} .0151889{col 43}{space 1} 1803.87{col 52}{space 3}0.000{col 60}{space 4} 27.36906{col 73}{space 3}  27.4286
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59102{col 38}{space 1}    59102{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26236 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,501
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  75972{txt}){col 67}= {res}  44921.53
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8199
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7134
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4229
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,973{txt}{col 51}Root MSE{col 67}= {res}    9.4218

{txt}{ralign 84:(Std. err. adjusted for {res:75,973} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.88045{col 32}{space 2}  .068714{col 43}{space 1} -187.45{col 52}{space 3}0.000{col 60}{space 4}-13.01512{col 73}{space 3}-12.74577
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.059695{col 32}{space 2} .0779349{col 43}{space 1}  -13.60{col 52}{space 3}0.000{col 60}{space 4}-1.212447{col 73}{space 3}-.9069429
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .3647388{col 32}{space 2} .5894428{col 43}{space 1}    0.62{col 52}{space 3}0.536{col 60}{space 4}-.7905662{col 73}{space 3} 1.520044
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -2.42163{col 32}{space 2} 1.008371{col 43}{space 1}   -2.40{col 52}{space 3}0.016{col 60}{space 4}-4.398033{col 73}{space 3} -.445228
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.57786{col 32}{space 2} .0115098{col 43}{space 1} 3004.21{col 52}{space 3}0.000{col 60}{space 4}  34.5553{col 73}{space 3} 34.60042
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75973{col 38}{space 1}    75973{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26236 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,501
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  75972{txt}){col 67}= {res}  52059.77
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9146
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8642
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7265
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    75,973{txt}{col 51}Root MSE{col 67}= {res}    6.4864

{txt}{ralign 84:(Std. err. adjusted for {res:75,973} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.27311{col 32}{space 2} .0738658{col 43}{space 1} -274.46{col 52}{space 3}0.000{col 60}{space 4}-20.41789{col 73}{space 3}-20.12833
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}  .174534{col 32}{space 2} .0751803{col 43}{space 1}    2.32{col 52}{space 3}0.020{col 60}{space 4} .0271809{col 73}{space 3}  .321887
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .7427249{col 32}{space 2} .5892426{col 43}{space 1}    1.26{col 52}{space 3}0.208{col 60}{space 4}-.4121877{col 73}{space 3} 1.897638
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.655859{col 32}{space 2} 1.008169{col 43}{space 1}   -3.63{col 52}{space 3}0.000{col 60}{space 4}-5.631865{col 73}{space 3}-1.679853
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.02936{col 32}{space 2} .0365578{col 43}{space 1} -383.76{col 52}{space 3}0.000{col 60}{space 4}-14.10101{col 73}{space 3} -13.9577
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.18341{col 32}{space 2} .0236031{col 43}{space 1} 1744.83{col 52}{space 3}0.000{col 60}{space 4} 41.13715{col 73}{space 3} 41.22967
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    75973{col 38}{space 1}    75973{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 32106 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   118,204
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  59101{txt}){col 67}= {res}  10580.82
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9374
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8747
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4045
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    59,102{txt}{col 51}Root MSE{col 67}= {res}    5.2239

{txt}{ralign 84:(Std. err. adjusted for {res:59,102} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-6.125122{col 32}{space 2} .0630641{col 43}{space 1}  -97.13{col 52}{space 3}0.000{col 60}{space 4}-6.248728{col 73}{space 3}-6.001516
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .0539401{col 32}{space 2}  .071431{col 43}{space 1}    0.76{col 52}{space 3}0.450{col 60}{space 4}-.0860649{col 73}{space 3} .1939451
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} 1.171208{col 32}{space 2} .6933768{col 43}{space 1}    1.69{col 52}{space 3}0.091{col 60}{space 4}-.1878129{col 73}{space 3}  2.53023
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2} -3.15944{col 32}{space 2} 1.121949{col 43}{space 1}   -2.82{col 52}{space 3}0.005{col 60}{space 4}-5.358466{col 73}{space 3}-.9604152
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 27.40359{col 32}{space 2} .0151942{col 43}{space 1} 1803.56{col 52}{space 3}0.000{col 60}{space 4} 27.37381{col 73}{space 3} 27.43337
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    59102{col 38}{space 1}    59102{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26256 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,554
{txt}Absorbing 1 HDFE group{col 51}F({res}   4{txt},{res}  75999{txt}){col 67}= {res}  44959.48
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.8198
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7133
{txt}{col 51}Within R-sq.{col 67}= {res}    0.4232
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,000{txt}{col 51}Root MSE{col 67}= {res}    9.4321

{txt}{ralign 84:(Std. err. adjusted for {res:76,000} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-12.93867{col 32}{space 2} .0689393{col 43}{space 1} -187.68{col 52}{space 3}0.000{col 60}{space 4}-13.07379{col 73}{space 3}-12.80355
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}-1.010154{col 32}{space 2} .0781405{col 43}{space 1}  -12.93{col 52}{space 3}0.000{col 60}{space 4}-1.163308{col 73}{space 3}-.8569986
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .4229602{col 32}{space 2} .5894691{col 43}{space 1}    0.72{col 52}{space 3}0.473{col 60}{space 4}-.7323963{col 73}{space 3} 1.578317
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-2.471172{col 32}{space 2} 1.008387{col 43}{space 1}   -2.45{col 52}{space 3}0.014{col 60}{space 4}-4.447605{col 73}{space 3}-.4947382
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 34.59153{col 32}{space 2}  .011524{col 43}{space 1} 3001.69{col 52}{space 3}0.000{col 60}{space 4} 34.56894{col 73}{space 3} 34.61411
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76000{col 38}{space 1}    76000{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}
{res}{txt}(dropped 26256 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}note: {res}1bn.ep{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}1bn.ep#1bn.ciutadella{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}{txt}note: 1.ep omitted because of collinearity
{txt}note: 1.ciutadella omitted because of collinearity
{txt}note: 1.ep#1.ciutadella omitted because of collinearity
{txt}note: 3.period omitted because of collinearity
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}   204,554
{txt}Absorbing 1 HDFE group{col 51}F({res}   5{txt},{res}  75999{txt}){col 67}= {res}  52101.71
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.9146
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8642
{txt}{col 51}Within R-sq.{col 67}= {res}    0.7267
{txt}{col 1}Number of clusters ({res}mesa_code_elecspecific{txt}) {col 30}= {res}    76,000{txt}{col 51}Root MSE{col 67}= {res}    6.4921

{txt}{ralign 84:(Std. err. adjusted for {res:76,000} clusters in {res:mesa_code_elecspecific})}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}      pp_voteshare{col 20}{c |} Coefficient{col 32}  std. err.{col 44}      t{col 52}   P>|t|{col 60}     [95% con{col 73}f. interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}1.post {c |}{col 20}{res}{space 2}-20.34266{col 32}{space 2}  .074094{col 43}{space 1} -274.55{col 52}{space 3}0.000{col 60}{space 4}-20.48789{col 73}{space 3}-20.19744
{txt}{space 14}1.ep {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 11}post#ep {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .2296582{col 32}{space 2} .0753856{col 43}{space 1}    3.05{col 52}{space 3}0.002{col 60}{space 4} .0819029{col 73}{space 3} .3774136
{txt}{space 18} {c |}
{space 6}1.ciutadella {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 3}post#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2} .8035429{col 32}{space 2}  .589269{col 43}{space 1}    1.36{col 52}{space 3}0.173{col 60}{space 4}-.3514214{col 73}{space 3} 1.958507
{txt}{space 18} {c |}
{space 5}ep#ciutadella {c |}
{space 14}1 1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
post#ep#ciutadella {c |}
{space 12}1 1 1  {c |}{col 20}{res}{space 2}-3.710984{col 32}{space 2} 1.008184{col 43}{space 1}   -3.68{col 52}{space 3}0.000{col 60}{space 4} -5.68702{col 73}{space 3}-1.734947
{txt}{space 18} {c |}
{space 12}period {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-14.04682{col 32}{space 2} .0365658{col 43}{space 1} -384.15{col 52}{space 3}0.000{col 60}{space 4}-14.11849{col 73}{space 3}-13.97516
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 41.20477{col 32}{space 2}  .023623{col 43}{space 1} 1744.27{col 52}{space 3}0.000{col 60}{space 4} 41.15847{col 73}{space 3} 41.25107
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 24}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}            Absorbed FE{col 25}{c |} Categories{col 38} - Redundant{col 50}  = Num. Coefs{col 65}{c |}
{res}{col 1}{text}{hline 24}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text} mesa_code_elecspecific{col 25}{c |}{space 1}    76000{col 38}{space 1}    76000{col 50}{result}{space 1}        0{col 64}{text}*{col 65}{c |}
{res}{col 1}{text}{hline 24}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}{p 0 4 2}
file {bf}
01_data/jackknives_ddd.dta{rm}
saved
{p_end}

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured6.do"
{txt}
{com}. ** NOTE: THIS DO-FILE IS PRESENTED WITH THE AIM OF BACKING THE CLAIM THAT THE INTERACTION BETWEEN VOTING BOOTH USE AND MUNICIPALITY SIZE IS STATISTICALLY SIGNIFICANT, AS REPORTED IN THE APPENDIX TEXT DISCUSSING FIGURE D.6
. 
. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. ** HTE based on municipality size
. regr cabine_use pp_dummy##c.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,847
                                                {txt}F(3, 1843)        =  {res}    76.07
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0865
                                                {txt}Root MSE          =    {res} .47526

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}       cabine_use{col 19}{c |} Coefficient{col 31}  std. err.{col 43}      t{col 51}   P>|t|{col 59}     [95% con{col 72}f. interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}1.pp_dummy {c |}{col 19}{res}{space 2} .2789992{col 31}{space 2}  .069667{col 42}{space 1}    4.00{col 51}{space 3}0.000{col 59}{space 4} .1423647{col 72}{space 3} .4156337
{txt}{space 11}TAMUNI {c |}{col 19}{res}{space 2}-.0775385{col 31}{space 2} .0065797{col 42}{space 1}  -11.78{col 51}{space 3}0.000{col 59}{space 4}-.0904428{col 72}{space 3}-.0646341
{txt}{space 17} {c |}
pp_dummy#c.TAMUNI {c |}
{space 15}1  {c |}{col 19}{res}{space 2}-.0412749{col 31}{space 2} .0153465{col 42}{space 1}   -2.69{col 51}{space 3}0.007{col 59}{space 4}-.0713732{col 72}{space 3}-.0111765
{txt}{space 17} {c |}
{space 12}_cons {c |}{col 19}{res}{space 2} .7301755{col 31}{space 2} .0299819{col 42}{space 1}   24.35{col 51}{space 3}0.000{col 59}{space 4} .6713734{col 72}{space 3} .7889775
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured7_1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Fake model to start the data
. regr pp_dummy CCAA

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     3,376
{txt}{hline 13}{c +}{hline 34}   F(1, 3374)      = {res}     0.01
{txt}       Model {c |} {res} .001511648         1  .001511648   {txt}Prob > F        ={res}    0.9221
{txt}    Residual {c |} {res} 533.401332     3,374  .158091681   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0003
{txt}       Total {c |} {res} 533.402844     3,375  .158045287   {txt}Root MSE        =   {res} .39761

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    pp_dummy{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}CCAA {c |}{col 14}{res}{space 2} .0001329{col 26}{space 2} .0013588{col 37}{space 1}    0.10{col 46}{space 3}0.922{col 54}{space 4}-.0025313{col 67}{space 3} .0027971
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1955201{col 26}{space 2} .0137159{col 37}{space 1}   14.26{col 46}{space 3}0.000{col 54}{space 4} .1686279{col 67}{space 3} .2224123
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regsave CCAA using 01_data/survey_data.dta, ci level(95) replace addlabel ///
> (Removed, fake, Model, fake,  FE, fake)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. * Actual analyses
. regr cabine_use pp_dummy i.income age age_sq i.education i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(42, 1313)       =  {res}    20.34
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2486
                                                {txt}Root MSE          =    {res} .43998

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0957879{col 45}{space 2} .0348476{col 56}{space 1}    2.75{col 65}{space 3}0.006{col 73}{space 4} .0274248{col 86}{space 3} .1641509
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} -.001077{col 45}{space 2} .0901508{col 56}{space 1}   -0.01{col 65}{space 3}0.990{col 73}{space 4}-.1779323{col 86}{space 3} .1757782
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0023462{col 45}{space 2} .0561697{col 56}{space 1}    0.04{col 65}{space 3}0.967{col 73}{space 4}-.1078461{col 86}{space 3} .1125384
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0300031{col 45}{space 2} .0442628{col 56}{space 1}   -0.68{col 65}{space 3}0.498{col 73}{space 4}-.1168367{col 86}{space 3} .0568304
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0399661{col 45}{space 2} .0416178{col 56}{space 1}   -0.96{col 65}{space 3}0.337{col 73}{space 4}-.1216108{col 86}{space 3} .0416785
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0142827{col 45}{space 2} .0429925{col 56}{space 1}   -0.33{col 65}{space 3}0.740{col 73}{space 4}-.0986242{col 86}{space 3} .0700587
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0151249{col 45}{space 2}  .050847{col 56}{space 1}    0.30{col 65}{space 3}0.766{col 73}{space 4}-.0846254{col 86}{space 3} .1148752
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0189724{col 45}{space 2} .0701883{col 56}{space 1}   -0.27{col 65}{space 3}0.787{col 73}{space 4}-.1566659{col 86}{space 3}  .118721
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1608525{col 45}{space 2} .1087852{col 56}{space 1}    1.48{col 65}{space 3}0.139{col 73}{space 4}-.0525594{col 86}{space 3} .3742643
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4173938{col 45}{space 2} .1726096{col 56}{space 1}   -2.42{col 65}{space 3}0.016{col 73}{space 4}-.7560146{col 86}{space 3} -.078773
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0347416{col 45}{space 2} .2096841{col 56}{space 1}    0.17{col 65}{space 3}0.868{col 73}{space 4}-.3766109{col 86}{space 3} .4460941
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0009516{col 45}{space 2}  .004497{col 56}{space 1}   -0.21{col 65}{space 3}0.832{col 73}{space 4}-.0097737{col 86}{space 3} .0078705
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000138{col 45}{space 2} .0000469{col 56}{space 1}   -0.29{col 65}{space 3}0.769{col 73}{space 4}-.0001058{col 86}{space 3} .0000782
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} -.056612{col 45}{space 2} .1050251{col 56}{space 1}   -0.54{col 65}{space 3}0.590{col 73}{space 4}-.2626473{col 86}{space 3} .1494234
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1352267{col 45}{space 2}  .105961{col 56}{space 1}   -1.28{col 65}{space 3}0.202{col 73}{space 4} -.343098{col 86}{space 3} .0726446
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.164935{col 45}{space 2} .1076425{col 56}{space 1}   -1.53{col 65}{space 3}0.126{col 73}{space 4}-.3761051{col 86}{space 3}  .046235
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0864042{col 45}{space 2} .1068618{col 56}{space 1}   -0.81{col 65}{space 3}0.419{col 73}{space 4}-.2960427{col 86}{space 3} .1232342
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1048523{col 45}{space 2} .1082154{col 56}{space 1}   -0.97{col 65}{space 3}0.333{col 73}{space 4}-.3171462{col 86}{space 3} .1074417
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0017008{col 45}{space 2}  .059567{col 56}{space 1}    0.03{col 65}{space 3}0.977{col 73}{space 4}-.1151561{col 86}{space 3} .1185576
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1301541{col 45}{space 2} .0579844{col 56}{space 1}   -2.24{col 65}{space 3}0.025{col 73}{space 4}-.2439062{col 86}{space 3}-.0164019
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1793708{col 45}{space 2} .0643594{col 56}{space 1}   -2.79{col 65}{space 3}0.005{col 73}{space 4}-.3056294{col 86}{space 3}-.0531123
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2218752{col 45}{space 2} .0597661{col 56}{space 1}   -3.71{col 65}{space 3}0.000{col 73}{space 4}-.3391226{col 86}{space 3}-.1046278
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.385478{col 45}{space 2} .0678563{col 56}{space 1}   -5.68{col 65}{space 3}0.000{col 73}{space 4}-.5185966{col 86}{space 3}-.2523593
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2440431{col 45}{space 2} .0635046{col 56}{space 1}   -3.84{col 65}{space 3}0.000{col 73}{space 4}-.3686246{col 86}{space 3}-.1194615
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0247428{col 45}{space 2} .0687962{col 56}{space 1}   -0.36{col 65}{space 3}0.719{col 73}{space 4}-.1597053{col 86}{space 3} .1102198
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2284282{col 45}{space 2} .0726127{col 56}{space 1}   -3.15{col 65}{space 3}0.002{col 73}{space 4}-.3708778{col 86}{space 3}-.0859785
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1880572{col 45}{space 2} .0775644{col 56}{space 1}   -2.42{col 65}{space 3}0.015{col 73}{space 4}-.3402208{col 86}{space 3}-.0358935
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3629672{col 45}{space 2} .0536087{col 56}{space 1}    6.77{col 65}{space 3}0.000{col 73}{space 4} .2577992{col 86}{space 3} .4681353
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0630006{col 45}{space 2} .0685758{col 56}{space 1}   -0.92{col 65}{space 3}0.358{col 73}{space 4}-.1975306{col 86}{space 3} .0715294
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0018541{col 45}{space 2} .0711443{col 56}{space 1}    0.03{col 65}{space 3}0.979{col 73}{space 4}-.1377148{col 86}{space 3}  .141423
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0425821{col 45}{space 2} .0711596{col 56}{space 1}    0.60{col 65}{space 3}0.550{col 73}{space 4} -.097017{col 86}{space 3} .1821811
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} -.444581{col 45}{space 2} .0481774{col 56}{space 1}   -9.23{col 65}{space 3}0.000{col 73}{space 4}-.5390941{col 86}{space 3}-.3500679
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0828788{col 45}{space 2} .0544282{col 56}{space 1}   -1.52{col 65}{space 3}0.128{col 73}{space 4}-.1896546{col 86}{space 3}  .023897
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1510554{col 45}{space 2}   .06112{col 56}{space 1}    2.47{col 65}{space 3}0.014{col 73}{space 4} .0311519{col 86}{space 3} .2709589
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.032895{col 45}{space 2}  .072211{col 56}{space 1}   -0.46{col 65}{space 3}0.649{col 73}{space 4}-.1745565{col 86}{space 3} .1087666
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3992186{col 45}{space 2} .0472524{col 56}{space 1}   -8.45{col 65}{space 3}0.000{col 73}{space 4}-.4919171{col 86}{space 3}-.3065202
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1317411{col 45}{space 2} .0662411{col 56}{space 1}    1.99{col 65}{space 3}0.047{col 73}{space 4} .0017911{col 86}{space 3}  .261691
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2051692{col 45}{space 2} .0911423{col 56}{space 1}   -2.25{col 65}{space 3}0.025{col 73}{space 4}-.3839696{col 86}{space 3}-.0263689
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.121255{col 45}{space 2} .0885573{col 56}{space 1}   -1.37{col 65}{space 3}0.171{col 73}{space 4}-.2949842{col 86}{space 3} .0524743
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0740735{col 45}{space 2} .1061093{col 56}{space 1}   -0.70{col 65}{space 3}0.485{col 73}{space 4}-.2822357{col 86}{space 3} .1340887
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2552348{col 45}{space 2} .0872976{col 56}{space 1}    2.92{col 65}{space 3}0.004{col 73}{space 4} .0839769{col 86}{space 3} .4264928
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1304824{col 45}{space 2} .1161583{col 56}{space 1}    1.12{col 65}{space 3}0.262{col 73}{space 4}-.0973938{col 86}{space 3} .3583585
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9206396{col 45}{space 2} .1454832{col 56}{space 1}    6.33{col 65}{space 3}0.000{col 73}{space 4} .6352345{col 86}{space 3} 1.206045
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Female, Model, cabine_use, FE, With region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female age age_sq i.education i.TAMUNI  i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,845
                                                {txt}{help j_robustsingular:F(33, 1810) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.2598
                                                {txt}Root MSE          =    {res} .43151

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0674998{col 45}{space 2} .0291517{col 56}{space 1}    2.32{col 65}{space 3}0.021{col 73}{space 4} .0103253{col 86}{space 3} .1246744
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0145121{col 45}{space 2}   .02034{col 56}{space 1}   -0.71{col 65}{space 3}0.476{col 73}{space 4}-.0544044{col 86}{space 3} .0253803
{txt}{space 28}age {c |}{col 33}{res}{space 2}-.0021856{col 45}{space 2} .0034763{col 56}{space 1}   -0.63{col 65}{space 3}0.530{col 73}{space 4}-.0090034{col 86}{space 3} .0046323
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} 9.29e-06{col 45}{space 2} .0000361{col 56}{space 1}    0.26{col 65}{space 3}0.797{col 73}{space 4}-.0000615{col 86}{space 3} .0000801
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0019428{col 45}{space 2} .0745737{col 56}{space 1}   -0.03{col 65}{space 3}0.979{col 73}{space 4}-.1482024{col 86}{space 3} .1443168
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0400532{col 45}{space 2} .0745697{col 56}{space 1}   -0.54{col 65}{space 3}0.591{col 73}{space 4}-.1863049{col 86}{space 3} .1061984
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0787268{col 45}{space 2} .0753213{col 56}{space 1}   -1.05{col 65}{space 3}0.296{col 73}{space 4}-.2264527{col 86}{space 3}  .068999
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} -.023343{col 45}{space 2}  .074792{col 56}{space 1}   -0.31{col 65}{space 3}0.755{col 73}{space 4}-.1700308{col 86}{space 3} .1233448
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0208023{col 45}{space 2} .0738584{col 56}{space 1}   -0.28{col 65}{space 3}0.778{col 73}{space 4}-.1656589{col 86}{space 3} .1240543
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2} .0288464{col 45}{space 2} .0832493{col 56}{space 1}    0.35{col 65}{space 3}0.729{col 73}{space 4}-.1344285{col 86}{space 3} .1921212
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0291341{col 45}{space 2} .0506066{col 56}{space 1}   -0.58{col 65}{space 3}0.565{col 73}{space 4}-.1283876{col 86}{space 3} .0701194
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1829577{col 45}{space 2} .0480701{col 56}{space 1}   -3.81{col 65}{space 3}0.000{col 73}{space 4}-.2772363{col 86}{space 3} -.088679
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1905932{col 45}{space 2} .0539498{col 56}{space 1}   -3.53{col 65}{space 3}0.000{col 73}{space 4}-.2964036{col 86}{space 3}-.0847829
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2439667{col 45}{space 2} .0492202{col 56}{space 1}   -4.96{col 65}{space 3}0.000{col 73}{space 4} -.340501{col 86}{space 3}-.1474324
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4011388{col 45}{space 2} .0586422{col 56}{space 1}   -6.84{col 65}{space 3}0.000{col 73}{space 4}-.5161523{col 86}{space 3}-.2861252
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}  -.28522{col 45}{space 2} .0505732{col 56}{space 1}   -5.64{col 65}{space 3}0.000{col 73}{space 4}-.3844079{col 86}{space 3} -.186032
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0551116{col 45}{space 2} .0616078{col 56}{space 1}   -0.89{col 65}{space 3}0.371{col 73}{space 4}-.1759416{col 86}{space 3} .0657183
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2207104{col 45}{space 2} .0654879{col 56}{space 1}   -3.37{col 65}{space 3}0.001{col 73}{space 4}-.3491502{col 86}{space 3}-.0922706
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.0924657{col 45}{space 2} .0626674{col 56}{space 1}   -1.48{col 65}{space 3}0.140{col 73}{space 4}-.2153738{col 86}{space 3} .0304424
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3773672{col 45}{space 2} .0488085{col 56}{space 1}    7.73{col 65}{space 3}0.000{col 73}{space 4} .2816404{col 86}{space 3} .4730941
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0575658{col 45}{space 2} .0619314{col 56}{space 1}   -0.93{col 65}{space 3}0.353{col 73}{space 4}-.1790304{col 86}{space 3} .0638989
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0361605{col 45}{space 2} .0648208{col 56}{space 1}    0.56{col 65}{space 3}0.577{col 73}{space 4} -.090971{col 86}{space 3} .1632921
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}-.0263129{col 45}{space 2} .0638826{col 56}{space 1}   -0.41{col 65}{space 3}0.680{col 73}{space 4}-.1516043{col 86}{space 3} .0989785
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4658812{col 45}{space 2} .0367563{col 56}{space 1}  -12.67{col 65}{space 3}0.000{col 73}{space 4}-.5379705{col 86}{space 3} -.393792
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0647434{col 45}{space 2} .0504271{col 56}{space 1}   -1.28{col 65}{space 3}0.199{col 73}{space 4}-.1636449{col 86}{space 3} .0341581
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1306415{col 45}{space 2} .0585139{col 56}{space 1}    2.23{col 65}{space 3}0.026{col 73}{space 4} .0158796{col 86}{space 3} .2454033
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0714428{col 45}{space 2} .0623494{col 56}{space 1}   -1.15{col 65}{space 3}0.252{col 73}{space 4}-.1937271{col 86}{space 3} .0508415
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3907392{col 45}{space 2} .0411273{col 56}{space 1}   -9.50{col 65}{space 3}0.000{col 73}{space 4}-.4714011{col 86}{space 3}-.3100772
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1709927{col 45}{space 2} .0612192{col 56}{space 1}    2.79{col 65}{space 3}0.005{col 73}{space 4} .0509249{col 86}{space 3} .2910604
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1780008{col 45}{space 2} .0840119{col 56}{space 1}   -2.12{col 65}{space 3}0.034{col 73}{space 4}-.3427713{col 86}{space 3}-.0132303
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1221997{col 45}{space 2} .0757116{col 56}{space 1}   -1.61{col 65}{space 3}0.107{col 73}{space 4} -.270691{col 86}{space 3} .0262916
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} .0226474{col 45}{space 2}  .070068{col 56}{space 1}    0.32{col 65}{space 3}0.747{col 73}{space 4}-.1147752{col 86}{space 3}   .16007
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2973934{col 45}{space 2} .0711654{col 56}{space 1}    4.18{col 65}{space 3}0.000{col 73}{space 4} .1578184{col 86}{space 3} .4369683
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1273588{col 45}{space 2} .1165308{col 56}{space 1}    1.09{col 65}{space 3}0.275{col 73}{space 4}-.1011903{col 86}{space 3} .3559079
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .8608997{col 45}{space 2} .1122623{col 56}{space 1}    7.67{col 65}{space 3}0.000{col 73}{space 4} .6407224{col 86}{space 3} 1.081077
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Income, Model, cabine_use, FE, With region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female i.income i.education i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(41, 1314)       =  {res}    20.11
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2456
                                                {txt}Root MSE          =    {res} .44072

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0864787{col 45}{space 2} .0343256{col 56}{space 1}    2.52{col 65}{space 3}0.012{col 73}{space 4} .0191399{col 86}{space 3} .1538176
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0226514{col 45}{space 2} .0258262{col 56}{space 1}   -0.88{col 65}{space 3}0.381{col 73}{space 4}-.0733164{col 86}{space 3} .0280136
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0086103{col 45}{space 2}  .089364{col 56}{space 1}   -0.10{col 65}{space 3}0.923{col 73}{space 4} -.183922{col 86}{space 3} .1667015
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0149642{col 45}{space 2} .0556575{col 56}{space 1}   -0.27{col 65}{space 3}0.788{col 73}{space 4}-.1241515{col 86}{space 3}  .094223
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} -.052723{col 45}{space 2} .0433626{col 56}{space 1}   -1.22{col 65}{space 3}0.224{col 73}{space 4}-.1377904{col 86}{space 3} .0323444
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0636647{col 45}{space 2} .0405498{col 56}{space 1}   -1.57{col 65}{space 3}0.117{col 73}{space 4}-.1432141{col 86}{space 3} .0158847
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0478666{col 45}{space 2}  .041196{col 56}{space 1}   -1.16{col 65}{space 3}0.245{col 73}{space 4}-.1286838{col 86}{space 3} .0329505
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0314156{col 45}{space 2} .0496384{col 56}{space 1}   -0.63{col 65}{space 3}0.527{col 73}{space 4}-.1287947{col 86}{space 3} .0659635
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0719645{col 45}{space 2} .0696943{col 56}{space 1}   -1.03{col 65}{space 3}0.302{col 73}{space 4}-.2086888{col 86}{space 3} .0647598
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1204304{col 45}{space 2} .1077805{col 56}{space 1}    1.12{col 65}{space 3}0.264{col 73}{space 4}-.0910103{col 86}{space 3} .3318711
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4588351{col 45}{space 2} .1931996{col 56}{space 1}   -2.37{col 65}{space 3}0.018{col 73}{space 4}-.8378484{col 86}{space 3}-.0798218
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0296177{col 45}{space 2} .2056712{col 56}{space 1}   -0.14{col 65}{space 3}0.886{col 73}{space 4}-.4330974{col 86}{space 3} .3738621
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0361325{col 45}{space 2} .1039995{col 56}{space 1}   -0.35{col 65}{space 3}0.728{col 73}{space 4}-.2401556{col 86}{space 3} .1678906
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0755646{col 45}{space 2} .1009385{col 56}{space 1}   -0.75{col 65}{space 3}0.454{col 73}{space 4}-.2735828{col 86}{space 3} .1224536
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0940878{col 45}{space 2} .1019135{col 56}{space 1}   -0.92{col 65}{space 3}0.356{col 73}{space 4}-.2940187{col 86}{space 3} .1058431
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0132511{col 45}{space 2} .1004976{col 56}{space 1}   -0.13{col 65}{space 3}0.895{col 73}{space 4}-.2104044{col 86}{space 3} .1839023
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0259673{col 45}{space 2} .1019739{col 56}{space 1}   -0.25{col 65}{space 3}0.799{col 73}{space 4}-.2260168{col 86}{space 3} .1740821
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0145147{col 45}{space 2} .0588443{col 56}{space 1}    0.25{col 65}{space 3}0.805{col 73}{space 4}-.1009244{col 86}{space 3} .1299537
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1211587{col 45}{space 2} .0573144{col 56}{space 1}   -2.11{col 65}{space 3}0.035{col 73}{space 4}-.2335964{col 86}{space 3}-.0087209
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1724744{col 45}{space 2} .0641104{col 56}{space 1}   -2.69{col 65}{space 3}0.007{col 73}{space 4}-.2982443{col 86}{space 3}-.0467045
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2197435{col 45}{space 2} .0595873{col 56}{space 1}   -3.69{col 65}{space 3}0.000{col 73}{space 4}-.3366401{col 86}{space 3}-.1028468
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3863474{col 45}{space 2} .0678011{col 56}{space 1}   -5.70{col 65}{space 3}0.000{col 73}{space 4}-.5193576{col 86}{space 3}-.2533371
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2403842{col 45}{space 2} .0636219{col 56}{space 1}   -3.78{col 65}{space 3}0.000{col 73}{space 4}-.3651957{col 86}{space 3}-.1155727
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0217196{col 45}{space 2} .0689675{col 56}{space 1}   -0.31{col 65}{space 3}0.753{col 73}{space 4} -.157018{col 86}{space 3} .1135787
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2292904{col 45}{space 2} .0738414{col 56}{space 1}   -3.11{col 65}{space 3}0.002{col 73}{space 4}-.3741503{col 86}{space 3}-.0844306
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1826146{col 45}{space 2} .0781938{col 56}{space 1}   -2.34{col 65}{space 3}0.020{col 73}{space 4}-.3360129{col 86}{space 3}-.0292163
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3673781{col 45}{space 2} .0544255{col 56}{space 1}    6.75{col 65}{space 3}0.000{col 73}{space 4} .2606077{col 86}{space 3} .4741485
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0703577{col 45}{space 2} .0681678{col 56}{space 1}   -1.03{col 65}{space 3}0.302{col 73}{space 4}-.2040874{col 86}{space 3} .0633719
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0001302{col 45}{space 2} .0706644{col 56}{space 1}   -0.00{col 65}{space 3}0.999{col 73}{space 4}-.1387575{col 86}{space 3} .1384971
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0395916{col 45}{space 2} .0703832{col 56}{space 1}    0.56{col 65}{space 3}0.574{col 73}{space 4}-.0984841{col 86}{space 3} .1776674
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4454561{col 45}{space 2}  .048154{col 56}{space 1}   -9.25{col 65}{space 3}0.000{col 73}{space 4}-.5399233{col 86}{space 3}-.3509889
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0866453{col 45}{space 2}  .054465{col 56}{space 1}   -1.59{col 65}{space 3}0.112{col 73}{space 4}-.1934932{col 86}{space 3} .0202026
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1503952{col 45}{space 2} .0611948{col 56}{space 1}    2.46{col 65}{space 3}0.014{col 73}{space 4}  .030345{col 86}{space 3} .2704454
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0455742{col 45}{space 2} .0719359{col 56}{space 1}   -0.63{col 65}{space 3}0.526{col 73}{space 4} -.186696{col 86}{space 3} .0955476
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4029481{col 45}{space 2} .0469567{col 56}{space 1}   -8.58{col 65}{space 3}0.000{col 73}{space 4}-.4950664{col 86}{space 3}-.3108298
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1334052{col 45}{space 2} .0663566{col 56}{space 1}    2.01{col 65}{space 3}0.045{col 73}{space 4} .0032288{col 86}{space 3} .2635816
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2178523{col 45}{space 2} .0909574{col 56}{space 1}   -2.40{col 65}{space 3}0.017{col 73}{space 4}-.3962899{col 86}{space 3}-.0394147
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1294142{col 45}{space 2} .0891005{col 56}{space 1}   -1.45{col 65}{space 3}0.147{col 73}{space 4} -.304209{col 86}{space 3} .0453807
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0750915{col 45}{space 2} .1060319{col 56}{space 1}   -0.71{col 65}{space 3}0.479{col 73}{space 4}-.2831017{col 86}{space 3} .1329188
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2452185{col 45}{space 2} .0892339{col 56}{space 1}    2.75{col 65}{space 3}0.006{col 73}{space 4}  .070162{col 86}{space 3} .4202749
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .137509{col 45}{space 2} .1153538{col 56}{space 1}    1.19{col 65}{space 3}0.233{col 73}{space 4}-.0887888{col 86}{space 3} .3638068
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .8141097{col 45}{space 2} .1153003{col 56}{space 1}    7.06{col 65}{space 3}0.000{col 73}{space 4} .5879169{col 86}{space 3} 1.040302
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Age and age squared, Model, cabine_use, FE, With region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female i.income age age_sq i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,357
                                                {txt}F(38, 1318)       =  {res}    21.90
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2433
                                                {txt}Root MSE          =    {res} .44085

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0953134{col 45}{space 2} .0348335{col 56}{space 1}    2.74{col 65}{space 3}0.006{col 73}{space 4} .0269783{col 86}{space 3} .1636485
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0118322{col 45}{space 2} .0255946{col 56}{space 1}   -0.46{col 65}{space 3}0.644{col 73}{space 4}-.0620428{col 86}{space 3} .0383783
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0102937{col 45}{space 2} .0895186{col 56}{space 1}   -0.11{col 65}{space 3}0.908{col 73}{space 4}-.1859082{col 86}{space 3} .1653207
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0009798{col 45}{space 2} .0570797{col 56}{space 1}    0.02{col 65}{space 3}0.986{col 73}{space 4}-.1109973{col 86}{space 3} .1129568
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} -.022245{col 45}{space 2} .0447644{col 56}{space 1}   -0.50{col 65}{space 3}0.619{col 73}{space 4}-.1100623{col 86}{space 3} .0655722
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0379871{col 45}{space 2} .0424676{col 56}{space 1}   -0.89{col 65}{space 3}0.371{col 73}{space 4}-.1212987{col 86}{space 3} .0453244
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0166412{col 45}{space 2}  .043464{col 56}{space 1}   -0.38{col 65}{space 3}0.702{col 73}{space 4}-.1019073{col 86}{space 3} .0686249
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0083603{col 45}{space 2} .0502282{col 56}{space 1}    0.17{col 65}{space 3}0.868{col 73}{space 4}-.0901758{col 86}{space 3} .1068963
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0233192{col 45}{space 2} .0709317{col 56}{space 1}   -0.33{col 65}{space 3}0.742{col 73}{space 4}-.1624706{col 86}{space 3} .1158323
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1629351{col 45}{space 2} .1079003{col 56}{space 1}    1.51{col 65}{space 3}0.131{col 73}{space 4}-.0487399{col 86}{space 3} .3746101
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4100054{col 45}{space 2} .1794578{col 56}{space 1}   -2.28{col 65}{space 3}0.022{col 73}{space 4}-.7620595{col 86}{space 3}-.0579514
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0466677{col 45}{space 2} .2101682{col 56}{space 1}    0.22{col 65}{space 3}0.824{col 73}{space 4} -.365633{col 86}{space 3} .4589683
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0017396{col 45}{space 2} .0044334{col 56}{space 1}   -0.39{col 65}{space 3}0.695{col 73}{space 4}-.0104369{col 86}{space 3} .0069577
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-7.26e-08{col 45}{space 2} .0000453{col 56}{space 1}   -0.00{col 65}{space 3}0.999{col 73}{space 4}-.0000889{col 86}{space 3} .0000888
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0091586{col 45}{space 2} .0597221{col 56}{space 1}   -0.15{col 65}{space 3}0.878{col 73}{space 4}-.1263194{col 86}{space 3} .1080022
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} -.138285{col 45}{space 2} .0577692{col 56}{space 1}   -2.39{col 65}{space 3}0.017{col 73}{space 4}-.2516146{col 86}{space 3}-.0249554
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1878824{col 45}{space 2} .0642296{col 56}{space 1}   -2.93{col 65}{space 3}0.004{col 73}{space 4}-.3138857{col 86}{space 3}-.0618791
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2286637{col 45}{space 2} .0595941{col 56}{space 1}   -3.84{col 65}{space 3}0.000{col 73}{space 4}-.3455732{col 86}{space 3}-.1117541
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4023018{col 45}{space 2} .0673519{col 56}{space 1}   -5.97{col 65}{space 3}0.000{col 73}{space 4}-.5344305{col 86}{space 3}-.2701732
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2426352{col 45}{space 2} .0634106{col 56}{space 1}   -3.83{col 65}{space 3}0.000{col 73}{space 4} -.367032{col 86}{space 3}-.1182384
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0283901{col 45}{space 2} .0687772{col 56}{space 1}   -0.41{col 65}{space 3}0.680{col 73}{space 4}-.1633147{col 86}{space 3} .1065346
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2312678{col 45}{space 2} .0728832{col 56}{space 1}   -3.17{col 65}{space 3}0.002{col 73}{space 4}-.3742475{col 86}{space 3}-.0882881
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1874219{col 45}{space 2} .0776015{col 56}{space 1}   -2.42{col 65}{space 3}0.016{col 73}{space 4}-.3396578{col 86}{space 3}-.0351859
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}  .365054{col 45}{space 2} .0538801{col 56}{space 1}    6.78{col 65}{space 3}0.000{col 73}{space 4} .2593538{col 86}{space 3} .4707542
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0687249{col 45}{space 2} .0688453{col 56}{space 1}   -1.00{col 65}{space 3}0.318{col 73}{space 4}-.2037833{col 86}{space 3} .0663334
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0108389{col 45}{space 2}  .071637{col 56}{space 1}   -0.15{col 65}{space 3}0.880{col 73}{space 4} -.151374{col 86}{space 3} .1296961
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0451764{col 45}{space 2} .0714816{col 56}{space 1}    0.63{col 65}{space 3}0.527{col 73}{space 4}-.0950538{col 86}{space 3} .1854065
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4490346{col 45}{space 2} .0481205{col 56}{space 1}   -9.33{col 65}{space 3}0.000{col 73}{space 4}-.5434358{col 86}{space 3}-.3546335
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0897935{col 45}{space 2} .0540213{col 56}{space 1}   -1.66{col 65}{space 3}0.097{col 73}{space 4}-.1957706{col 86}{space 3} .0161836
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1491417{col 45}{space 2}  .061114{col 56}{space 1}    2.44{col 65}{space 3}0.015{col 73}{space 4} .0292504{col 86}{space 3} .2690329
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.038424{col 45}{space 2} .0723623{col 56}{space 1}   -0.53{col 65}{space 3}0.596{col 73}{space 4}-.1803819{col 86}{space 3}  .103534
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4129516{col 45}{space 2} .0468618{col 56}{space 1}   -8.81{col 65}{space 3}0.000{col 73}{space 4}-.5048834{col 86}{space 3}-.3210199
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1339735{col 45}{space 2}  .066263{col 56}{space 1}    2.02{col 65}{space 3}0.043{col 73}{space 4}  .003981{col 86}{space 3} .2639661
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2044968{col 45}{space 2} .0914296{col 56}{space 1}   -2.24{col 65}{space 3}0.025{col 73}{space 4}-.3838602{col 86}{space 3}-.0251335
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1146469{col 45}{space 2}  .088759{col 56}{space 1}   -1.29{col 65}{space 3}0.197{col 73}{space 4}-.2887712{col 86}{space 3} .0594774
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0938742{col 45}{space 2} .1044198{col 56}{space 1}   -0.90{col 65}{space 3}0.369{col 73}{space 4}-.2987214{col 86}{space 3}  .110973
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .238153{col 45}{space 2} .0872135{col 56}{space 1}    2.73{col 65}{space 3}0.006{col 73}{space 4} .0670606{col 86}{space 3} .4092455
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1249712{col 45}{space 2} .1161897{col 56}{space 1}    1.08{col 65}{space 3}0.282{col 73}{space 4}-.1029656{col 86}{space 3} .3529081
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .8303985{col 45}{space 2} .1144081{col 56}{space 1}    7.26{col 65}{space 3}0.000{col 73}{space 4} .6059566{col 86}{space 3}  1.05484
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Education, Model, cabine_use, FE, With region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str9}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female i.income age age_sq i.education i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(37, 1318)       =  {res}    16.16
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2079
                                                {txt}Root MSE          =    {res} .45088

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                   cabine_use{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}pp_dummy {c |}{col 31}{res}{space 2} .1028783{col 43}{space 2} .0366391{col 54}{space 1}    2.81{col 63}{space 3}0.005{col 71}{space 4}  .031001{col 84}{space 3} .1747556
{txt}{space 23}female {c |}{col 31}{res}{space 2}-.0160273{col 43}{space 2} .0265946{col 54}{space 1}   -0.60{col 63}{space 3}0.547{col 71}{space 4}-.0681997{col 84}{space 3}  .036145
{txt}{space 29} {c |}
{space 23}income {c |}
{space 7}Menos o igual a 300 €  {c |}{col 31}{res}{space 2}-.0192186{col 43}{space 2} .0920506{col 54}{space 1}   -0.21{col 63}{space 3}0.835{col 71}{space 4}-.1998004{col 84}{space 3} .1613632
{txt}{space 14}De 301 a 600 €  {c |}{col 31}{res}{space 2} .0023233{col 43}{space 2}  .056357{col 54}{space 1}    0.04{col 63}{space 3}0.967{col 71}{space 4}-.1082359{col 84}{space 3} .1128825
{txt}{space 14}De 601 a 900 €  {c |}{col 31}{res}{space 2} -.040951{col 43}{space 2} .0458988{col 54}{space 1}   -0.89{col 63}{space 3}0.372{col 71}{space 4}-.1309937{col 84}{space 3} .0490917
{txt}{space 12}De 901 a 1.200 €  {c |}{col 31}{res}{space 2}-.0465194{col 43}{space 2} .0426387{col 54}{space 1}   -1.09{col 63}{space 3}0.275{col 71}{space 4}-.1301665{col 84}{space 3} .0371277
{txt}{space 10}De 1.201 a 1.800 €  {c |}{col 31}{res}{space 2}-.0286426{col 43}{space 2} .0450929{col 54}{space 1}   -0.64{col 63}{space 3}0.525{col 71}{space 4}-.1171044{col 84}{space 3} .0598191
{txt}{space 10}De 1.801 a 2.400 €  {c |}{col 31}{res}{space 2} .0181631{col 43}{space 2} .0542462{col 54}{space 1}    0.33{col 63}{space 3}0.738{col 71}{space 4}-.0882552{col 84}{space 3} .1245813
{txt}{space 10}De 2.401 a 3.000 €  {c |}{col 31}{res}{space 2}-.0601569{col 43}{space 2} .0732573{col 54}{space 1}   -0.82{col 63}{space 3}0.412{col 71}{space 4}-.2038706{col 84}{space 3} .0835567
{txt}{space 10}De 3.001 a 4.500 €  {c |}{col 31}{res}{space 2} .1454376{col 43}{space 2} .1169574{col 54}{space 1}    1.24{col 63}{space 3}0.214{col 71}{space 4}-.0840053{col 84}{space 3} .3748805
{txt}{space 10}De 4.501 a 6.000 €  {c |}{col 31}{res}{space 2}-.4516595{col 43}{space 2}  .220487{col 54}{space 1}   -2.05{col 63}{space 3}0.041{col 71}{space 4}-.8842033{col 84}{space 3}-.0191158
{txt}{space 14}Más de 6.000 €  {c |}{col 31}{res}{space 2} .0620391{col 43}{space 2} .1814303{col 54}{space 1}    0.34{col 63}{space 3}0.732{col 71}{space 4}-.2938845{col 84}{space 3} .4179628
{txt}{space 29} {c |}
{space 26}age {c |}{col 31}{res}{space 2}-.0006323{col 43}{space 2} .0045696{col 54}{space 1}   -0.14{col 63}{space 3}0.890{col 71}{space 4}-.0095968{col 84}{space 3} .0083321
{txt}{space 23}age_sq {c |}{col 31}{res}{space 2}-.0000249{col 43}{space 2} .0000479{col 54}{space 1}   -0.52{col 63}{space 3}0.603{col 71}{space 4} -.000119{col 84}{space 3} .0000691
{txt}{space 29} {c |}
{space 20}education {c |}
{space 20}Primaria  {c |}{col 31}{res}{space 2} -.083871{col 43}{space 2} .1111912{col 54}{space 1}   -0.75{col 63}{space 3}0.451{col 71}{space 4}-.3020022{col 84}{space 3} .1342602
{txt}{space 9}Secundaria 1ª etapa  {c |}{col 31}{res}{space 2}-.1902146{col 43}{space 2} .1120268{col 54}{space 1}   -1.70{col 63}{space 3}0.090{col 71}{space 4}-.4099849{col 84}{space 3} .0295556
{txt}{space 9}Secundaria 2ª etapa  {c |}{col 31}{res}{space 2} -.239317{col 43}{space 2} .1133744{col 54}{space 1}   -2.11{col 63}{space 3}0.035{col 71}{space 4} -.461731{col 84}{space 3}-.0169029
{txt}{space 24}F.P.  {c |}{col 31}{res}{space 2}-.1535364{col 43}{space 2} .1128089{col 54}{space 1}   -1.36{col 63}{space 3}0.174{col 71}{space 4}-.3748409{col 84}{space 3} .0677682
{txt}{space 18}Superiores  {c |}{col 31}{res}{space 2}-.1880361{col 43}{space 2} .1139357{col 54}{space 1}   -1.65{col 63}{space 3}0.099{col 71}{space 4}-.4115511{col 84}{space 3}  .035479
{txt}{space 29} {c |}
{space 25}CCAA {c |}
{space 22}Aragón  {c |}{col 31}{res}{space 2}-.0444904{col 43}{space 2} .0737706{col 54}{space 1}   -0.60{col 63}{space 3}0.547{col 71}{space 4} -.189211{col 84}{space 3} .1002303
{txt}{space 4}Asturias (Principado de)  {c |}{col 31}{res}{space 2}-.2290086{col 43}{space 2} .0724692{col 54}{space 1}   -3.16{col 63}{space 3}0.002{col 71}{space 4} -.371176{col 84}{space 3}-.0868411
{txt}{space 13}Balears (Illes)  {c |}{col 31}{res}{space 2}-.2524172{col 43}{space 2} .0749139{col 54}{space 1}   -3.37{col 63}{space 3}0.001{col 71}{space 4}-.3993808{col 84}{space 3}-.1054537
{txt}{space 20}Canarias  {c |}{col 31}{res}{space 2} .3724001{col 43}{space 2} .0540057{col 54}{space 1}    6.90{col 63}{space 3}0.000{col 71}{space 4} .2664536{col 84}{space 3} .4783467
{txt}{space 19}Cantabria  {c |}{col 31}{res}{space 2} .0313388{col 43}{space 2} .0697236{col 54}{space 1}    0.45{col 63}{space 3}0.653{col 71}{space 4}-.1054425{col 84}{space 3} .1681201
{txt}{space 10}Castilla-La Mancha  {c |}{col 31}{res}{space 2} .0561067{col 43}{space 2} .0727523{col 54}{space 1}    0.77{col 63}{space 3}0.441{col 71}{space 4}-.0866163{col 84}{space 3} .1988296
{txt}{space 13}Castilla y León  {c |}{col 31}{res}{space 2} .1035009{col 43}{space 2} .0727375{col 54}{space 1}    1.42{col 63}{space 3}0.155{col 71}{space 4} -.039193{col 84}{space 3} .2461947
{txt}{space 20}Cataluña  {c |}{col 31}{res}{space 2}-.4189863{col 43}{space 2} .0448254{col 54}{space 1}   -9.35{col 63}{space 3}0.000{col 71}{space 4}-.5069232{col 84}{space 3}-.3310494
{txt}{space 8}Comunitat Valenciana  {c |}{col 31}{res}{space 2}-.0752346{col 43}{space 2} .0555555{col 54}{space 1}   -1.35{col 63}{space 3}0.176{col 71}{space 4}-.1842215{col 84}{space 3} .0337522
{txt}{space 17}Extremadura  {c |}{col 31}{res}{space 2} .2241791{col 43}{space 2} .0602339{col 54}{space 1}    3.72{col 63}{space 3}0.000{col 71}{space 4} .1060143{col 84}{space 3} .3423439
{txt}{space 21}Galicia  {c |}{col 31}{res}{space 2}  .037059{col 43}{space 2} .0728198{col 54}{space 1}    0.51{col 63}{space 3}0.611{col 71}{space 4}-.1057963{col 84}{space 3} .1799144
{txt}{space 7}Madrid (Comunidad de)  {c |}{col 31}{res}{space 2}-.4035885{col 43}{space 2} .0442189{col 54}{space 1}   -9.13{col 63}{space 3}0.000{col 71}{space 4}-.4903356{col 84}{space 3}-.3168414
{txt}{space 10}Murcia (Región de)  {c |}{col 31}{res}{space 2}  .088626{col 43}{space 2} .0668626{col 54}{space 1}    1.33{col 63}{space 3}0.185{col 71}{space 4}-.0425427{col 84}{space 3} .2197948
{txt}Navarra (Comunidad Foral de)  {c |}{col 31}{res}{space 2}-.0926747{col 43}{space 2} .0916679{col 54}{space 1}   -1.01{col 63}{space 3}0.312{col 71}{space 4}-.2725057{col 84}{space 3} .0871563
{txt}{space 18}País Vasco  {c |}{col 31}{res}{space 2} -.085018{col 43}{space 2} .0872441{col 54}{space 1}   -0.97{col 63}{space 3}0.330{col 71}{space 4}-.2561704{col 84}{space 3} .0861344
{txt}{space 18}Rioja (La)  {c |}{col 31}{res}{space 2}-.0447326{col 43}{space 2} .1081456{col 54}{space 1}   -0.41{col 63}{space 3}0.679{col 71}{space 4} -.256889{col 84}{space 3} .1674237
{txt}{space 2}Ceuta (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .2551961{col 43}{space 2}  .079848{col 54}{space 1}    3.20{col 63}{space 3}0.001{col 71}{space 4}  .098553{col 84}{space 3} .4118392
{txt}Melilla (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .1203762{col 43}{space 2} .1109581{col 54}{space 1}    1.08{col 63}{space 3}0.278{col 71}{space 4}-.0972976{col 84}{space 3}   .33805
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .8311999{col 43}{space 2} .1369459{col 54}{space 1}    6.07{col 63}{space 3}0.000{col 71}{space 4} .5625441{col 84}{space 3} 1.099856
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Mun Size, Model, cabine_use, FE, With region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str8}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy i.income age age_sq  i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(24, 1331)       =  {res}    16.85
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1165
                                                {txt}Root MSE          =    {res} .47387

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1309627{col 45}{space 2} .0373478{col 56}{space 1}    3.51{col 65}{space 3}0.000{col 73}{space 4} .0576957{col 86}{space 3} .2042297
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0384867{col 45}{space 2} .0914337{col 56}{space 1}    0.42{col 65}{space 3}0.674{col 73}{space 4}-.1408832{col 86}{space 3} .2178567
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0041144{col 45}{space 2} .0585368{col 56}{space 1}    0.07{col 65}{space 3}0.944{col 73}{space 4}  -.11072{col 86}{space 3} .1189488
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0227361{col 45}{space 2} .0480716{col 56}{space 1}   -0.47{col 65}{space 3}0.636{col 73}{space 4}-.1170405{col 86}{space 3} .0715684
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0526532{col 45}{space 2} .0452521{col 56}{space 1}   -1.16{col 65}{space 3}0.245{col 73}{space 4}-.1414263{col 86}{space 3} .0361199
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} -.051159{col 45}{space 2} .0461904{col 56}{space 1}   -1.11{col 65}{space 3}0.268{col 73}{space 4} -.141773{col 86}{space 3} .0394549
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.029117{col 45}{space 2} .0559339{col 56}{space 1}   -0.52{col 65}{space 3}0.603{col 73}{space 4}-.1388452{col 86}{space 3} .0806113
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.1108693{col 45}{space 2} .0771249{col 56}{space 1}   -1.44{col 65}{space 3}0.151{col 73}{space 4}-.2621689{col 86}{space 3} .0404302
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1019697{col 45}{space 2} .1092574{col 56}{space 1}    0.93{col 65}{space 3}0.351{col 73}{space 4}-.1123657{col 86}{space 3} .3163051
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4901884{col 45}{space 2} .0770843{col 56}{space 1}   -6.36{col 65}{space 3}0.000{col 73}{space 4}-.6414084{col 86}{space 3}-.3389684
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.082291{col 45}{space 2} .2505006{col 56}{space 1}   -0.33{col 65}{space 3}0.743{col 73}{space 4}-.5737099{col 86}{space 3}  .409128
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0023355{col 45}{space 2} .0047417{col 56}{space 1}    0.49{col 65}{space 3}0.622{col 73}{space 4}-.0069665{col 86}{space 3} .0116376
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000509{col 45}{space 2} .0000488{col 56}{space 1}   -1.04{col 65}{space 3}0.298{col 73}{space 4}-.0001467{col 86}{space 3}  .000045
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0629371{col 45}{space 2} .1145796{col 56}{space 1}   -0.55{col 65}{space 3}0.583{col 73}{space 4}-.2877135{col 86}{space 3} .1618393
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1594793{col 45}{space 2}  .114485{col 56}{space 1}   -1.39{col 65}{space 3}0.164{col 73}{space 4}-.3840701{col 86}{space 3} .0651114
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2281797{col 45}{space 2} .1159436{col 56}{space 1}   -1.97{col 65}{space 3}0.049{col 73}{space 4}-.4556318{col 86}{space 3}-.0007276
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1197025{col 45}{space 2} .1152759{col 56}{space 1}   -1.04{col 65}{space 3}0.299{col 73}{space 4}-.3458447{col 86}{space 3} .1064397
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1337901{col 45}{space 2} .1167254{col 56}{space 1}   -1.15{col 65}{space 3}0.252{col 73}{space 4}-.3627759{col 86}{space 3} .0951957
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0093359{col 45}{space 2} .0625942{col 56}{space 1}    0.15{col 65}{space 3}0.881{col 73}{space 4}-.1134581{col 86}{space 3}   .13213
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1271295{col 45}{space 2} .0600733{col 56}{space 1}   -2.12{col 65}{space 3}0.035{col 73}{space 4}-.2449782{col 86}{space 3}-.0092809
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1215937{col 45}{space 2} .0638493{col 56}{space 1}   -1.90{col 65}{space 3}0.057{col 73}{space 4}-.2468498{col 86}{space 3} .0036625
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} -.241599{col 45}{space 2} .0609706{col 56}{space 1}   -3.96{col 65}{space 3}0.000{col 73}{space 4} -.361208{col 86}{space 3}-.1219901
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3247061{col 45}{space 2} .0664179{col 56}{space 1}   -4.89{col 65}{space 3}0.000{col 73}{space 4}-.4550012{col 86}{space 3} -.194411
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.564044{col 45}{space 2}  .060347{col 56}{space 1}   -9.35{col 65}{space 3}0.000{col 73}{space 4}-.6824296{col 86}{space 3}-.4456583
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .8153522{col 45}{space 2} .1541388{col 56}{space 1}    5.29{col 65}{space 3}0.000{col 73}{space 4} .5129707{col 86}{space 3} 1.117734
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Female, Model, cabine_use, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str6}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female age age_sq  i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,845
                                                {txt}{help j_robustsingular:F(15, 1828) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.1085
                                                {txt}Root MSE          =    {res} .47124

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1255689{col 45}{space 2} .0311194{col 56}{space 1}    4.04{col 65}{space 3}0.000{col 73}{space 4} .0645356{col 86}{space 3} .1866023
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0098497{col 45}{space 2} .0221311{col 56}{space 1}   -0.45{col 65}{space 3}0.656{col 73}{space 4}-.0532545{col 86}{space 3} .0335551
{txt}{space 28}age {c |}{col 33}{res}{space 2}-.0017269{col 45}{space 2} .0037415{col 56}{space 1}   -0.46{col 65}{space 3}0.644{col 73}{space 4}-.0090649{col 86}{space 3} .0056111
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-5.04e-06{col 45}{space 2} .0000385{col 56}{space 1}   -0.13{col 65}{space 3}0.896{col 73}{space 4}-.0000806{col 86}{space 3} .0000705
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0011471{col 45}{space 2} .0827992{col 56}{space 1}   -0.01{col 65}{space 3}0.989{col 73}{space 4}-.1635381{col 86}{space 3}  .161244
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0559863{col 45}{space 2}  .080948{col 56}{space 1}   -0.69{col 65}{space 3}0.489{col 73}{space 4}-.2147466{col 86}{space 3}  .102774
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1382301{col 45}{space 2} .0817678{col 56}{space 1}   -1.69{col 65}{space 3}0.091{col 73}{space 4}-.2985983{col 86}{space 3}  .022138
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0651544{col 45}{space 2} .0811524{col 56}{space 1}   -0.80{col 65}{space 3}0.422{col 73}{space 4}-.2243155{col 86}{space 3} .0940066
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0619717{col 45}{space 2} .0802831{col 56}{space 1}   -0.77{col 65}{space 3}0.440{col 73}{space 4}-.2194279{col 86}{space 3} .0954846
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2} .4701996{col 45}{space 2} .0814924{col 56}{space 1}    5.77{col 65}{space 3}0.000{col 73}{space 4} .3103716{col 86}{space 3} .6300276
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0386395{col 45}{space 2} .0538224{col 56}{space 1}   -0.72{col 65}{space 3}0.473{col 73}{space 4}-.1441994{col 86}{space 3} .0669205
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1839573{col 45}{space 2} .0503451{col 56}{space 1}   -3.65{col 65}{space 3}0.000{col 73}{space 4}-.2826972{col 86}{space 3}-.0852174
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1378566{col 45}{space 2} .0544493{col 56}{space 1}   -2.53{col 65}{space 3}0.011{col 73}{space 4}-.2446459{col 86}{space 3}-.0310672
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2484199{col 45}{space 2} .0510168{col 56}{space 1}   -4.87{col 65}{space 3}0.000{col 73}{space 4}-.3484773{col 86}{space 3}-.1483625
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3106505{col 45}{space 2} .0577796{col 56}{space 1}   -5.38{col 65}{space 3}0.000{col 73}{space 4}-.4239716{col 86}{space 3}-.1973295
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.5995204{col 45}{space 2} .0482926{col 56}{space 1}  -12.41{col 65}{space 3}0.000{col 73}{space 4}-.6942349{col 86}{space 3}-.5048058
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .7965084{col 45}{space 2} .1203129{col 56}{space 1}    6.62{col 65}{space 3}0.000{col 73}{space 4} .5605433{col 86}{space 3} 1.032474
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Income, Model, cabine_use, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str6}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female i.income  i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(23, 1332)       =  {res}    20.02
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1121
                                                {txt}Root MSE          =    {res} .47488

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1224569{col 45}{space 2} .0368658{col 56}{space 1}    3.32{col 65}{space 3}0.001{col 73}{space 4} .0501356{col 86}{space 3} .1947783
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0209528{col 45}{space 2} .0275981{col 56}{space 1}   -0.76{col 65}{space 3}0.448{col 73}{space 4}-.0750932{col 86}{space 3} .0331875
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0343946{col 45}{space 2} .0911012{col 56}{space 1}    0.38{col 65}{space 3}0.706{col 73}{space 4}-.1443229{col 86}{space 3} .2131121
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0082742{col 45}{space 2} .0583012{col 56}{space 1}   -0.14{col 65}{space 3}0.887{col 73}{space 4}-.1226464{col 86}{space 3}  .106098
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0423855{col 45}{space 2} .0474336{col 56}{space 1}   -0.89{col 65}{space 3}0.372{col 73}{space 4}-.1354381{col 86}{space 3} .0506672
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0706219{col 45}{space 2} .0442215{col 56}{space 1}   -1.60{col 65}{space 3}0.111{col 73}{space 4}-.1573733{col 86}{space 3} .0161294
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0774796{col 45}{space 2} .0446761{col 56}{space 1}   -1.73{col 65}{space 3}0.083{col 73}{space 4}-.1651227{col 86}{space 3} .0101636
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0686095{col 45}{space 2} .0546098{col 56}{space 1}   -1.26{col 65}{space 3}0.209{col 73}{space 4}-.1757401{col 86}{space 3} .0385211
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.1568221{col 45}{space 2} .0756065{col 56}{space 1}   -2.07{col 65}{space 3}0.038{col 73}{space 4}-.3051429{col 86}{space 3}-.0085013
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0691292{col 45}{space 2}  .108312{col 56}{space 1}    0.64{col 65}{space 3}0.523{col 73}{space 4}-.1433514{col 86}{space 3} .2816099
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.5219331{col 45}{space 2} .0587615{col 56}{space 1}   -8.88{col 65}{space 3}0.000{col 73}{space 4}-.6372082{col 86}{space 3}-.4066581
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.1434336{col 45}{space 2} .2456946{col 56}{space 1}   -0.58{col 65}{space 3}0.559{col 73}{space 4}-.6254241{col 86}{space 3}  .338557
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0320781{col 45}{space 2} .1118255{col 56}{space 1}   -0.29{col 65}{space 3}0.774{col 73}{space 4}-.2514513{col 86}{space 3} .1872951
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} -.077552{col 45}{space 2} .1081084{col 56}{space 1}   -0.72{col 65}{space 3}0.473{col 73}{space 4}-.2896332{col 86}{space 3} .1345292
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1375996{col 45}{space 2} .1091946{col 56}{space 1}   -1.26{col 65}{space 3}0.208{col 73}{space 4}-.3518118{col 86}{space 3} .0766126
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0242251{col 45}{space 2} .1078487{col 56}{space 1}   -0.22{col 65}{space 3}0.822{col 73}{space 4} -.235797{col 86}{space 3} .1873468
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} -.033265{col 45}{space 2} .1091087{col 56}{space 1}   -0.30{col 65}{space 3}0.761{col 73}{space 4}-.2473087{col 86}{space 3} .1807786
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0194469{col 45}{space 2} .0621772{col 56}{space 1}    0.31{col 65}{space 3}0.755{col 73}{space 4} -.102529{col 86}{space 3} .1414228
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1194222{col 45}{space 2} .0595675{col 56}{space 1}   -2.00{col 65}{space 3}0.045{col 73}{space 4}-.2362786{col 86}{space 3}-.0025659
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} -.116029{col 45}{space 2}  .063584{col 56}{space 1}   -1.82{col 65}{space 3}0.068{col 73}{space 4}-.2407647{col 86}{space 3} .0087067
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2402308{col 45}{space 2} .0608223{col 56}{space 1}   -3.95{col 65}{space 3}0.000{col 73}{space 4}-.3595486{col 86}{space 3} -.120913
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3247101{col 45}{space 2} .0665002{col 56}{space 1}   -4.88{col 65}{space 3}0.000{col 73}{space 4}-.4551667{col 86}{space 3}-.1942534
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.5642708{col 45}{space 2} .0602846{col 56}{space 1}   -9.36{col 65}{space 3}0.000{col 73}{space 4}-.6825338{col 86}{space 3}-.4460078
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .7455011{col 45}{space 2} .1197144{col 56}{space 1}    6.23{col 65}{space 3}0.000{col 73}{space 4} .5106518{col 86}{space 3} .9803504
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Age and age squared, Model, cabine_use, FE, Without region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female i.income age age_sq i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,357
                                                {txt}F(20, 1336)       =  {res}    20.08
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1076
                                                {txt}Root MSE          =    {res} .47552

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1281729{col 45}{space 2} .0374295{col 56}{space 1}    3.42{col 65}{space 3}0.001{col 73}{space 4}  .054746{col 86}{space 3} .2015998
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0119173{col 45}{space 2} .0273853{col 56}{space 1}   -0.44{col 65}{space 3}0.664{col 73}{space 4}-.0656401{col 86}{space 3} .0418055
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0274461{col 45}{space 2} .0914479{col 56}{space 1}    0.30{col 65}{space 3}0.764{col 73}{space 4} -.151951{col 86}{space 3} .2068431
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0043346{col 45}{space 2} .0598821{col 56}{space 1}    0.07{col 65}{space 3}0.942{col 73}{space 4}-.1131386{col 86}{space 3} .1218079
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0094285{col 45}{space 2} .0486272{col 56}{space 1}   -0.19{col 65}{space 3}0.846{col 73}{space 4}-.1048226{col 86}{space 3} .0859656
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0497551{col 45}{space 2} .0459995{col 56}{space 1}   -1.08{col 65}{space 3}0.280{col 73}{space 4}-.1399942{col 86}{space 3} .0404841
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0551222{col 45}{space 2} .0467639{col 56}{space 1}   -1.18{col 65}{space 3}0.239{col 73}{space 4}-.1468609{col 86}{space 3} .0366165
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0359879{col 45}{space 2} .0547123{col 56}{space 1}   -0.66{col 65}{space 3}0.511{col 73}{space 4}-.1433192{col 86}{space 3} .0713434
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.1171892{col 45}{space 2} .0775714{col 56}{space 1}   -1.51{col 65}{space 3}0.131{col 73}{space 4}-.2693642{col 86}{space 3} .0349858
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1040575{col 45}{space 2} .1076192{col 56}{space 1}    0.97{col 65}{space 3}0.334{col 73}{space 4}-.1070636{col 86}{space 3} .3151787
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4783845{col 45}{space 2} .0635572{col 56}{space 1}   -7.53{col 65}{space 3}0.000{col 73}{space 4}-.6030672{col 86}{space 3}-.3537018
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0710014{col 45}{space 2} .2504963{col 56}{space 1}   -0.28{col 65}{space 3}0.777{col 73}{space 4}-.5624103{col 86}{space 3} .4204074
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0016945{col 45}{space 2} .0047413{col 56}{space 1}    0.36{col 65}{space 3}0.721{col 73}{space 4}-.0076067{col 86}{space 3} .0109957
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000355{col 45}{space 2} .0000482{col 56}{space 1}   -0.74{col 65}{space 3}0.461{col 73}{space 4}  -.00013{col 86}{space 3}  .000059
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0051268{col 45}{space 2} .0627265{col 56}{space 1}   -0.08{col 65}{space 3}0.935{col 73}{space 4}-.1281801{col 86}{space 3} .1179264
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1389096{col 45}{space 2} .0597338{col 56}{space 1}   -2.33{col 65}{space 3}0.020{col 73}{space 4}-.2560919{col 86}{space 3}-.0217273
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1393537{col 45}{space 2} .0636152{col 56}{space 1}   -2.19{col 65}{space 3}0.029{col 73}{space 4}-.2641501{col 86}{space 3}-.0145572
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2542914{col 45}{space 2} .0605593{col 56}{space 1}   -4.20{col 65}{space 3}0.000{col 73}{space 4} -.373093{col 86}{space 3}-.1354899
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3471865{col 45}{space 2} .0657148{col 56}{space 1}   -5.28{col 65}{space 3}0.000{col 73}{space 4} -.476102{col 86}{space 3} -.218271
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.5718232{col 45}{space 2} .0601731{col 56}{space 1}   -9.50{col 65}{space 3}0.000{col 73}{space 4}-.6898673{col 86}{space 3}-.4537792
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .6828453{col 45}{space 2} .1169791{col 56}{space 1}    5.84{col 65}{space 3}0.000{col 73}{space 4} .4533625{col 86}{space 3}  .912328
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Education, Model, cabine_use, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str9}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
. regr cabine_use pp_dummy female i.income age age_sq i.education, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(19, 1336)       =  {res}    38.00
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0371
                                                {txt}Root MSE          =    {res} .49377

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}            cabine_use{col 24}{c |} Coefficient{col 36}  std. err.{col 48}      t{col 56}   P>|t|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}pp_dummy {c |}{col 24}{res}{space 2} .1444323{col 36}{space 2} .0399454{col 47}{space 1}    3.62{col 56}{space 3}0.000{col 64}{space 4} .0660698{col 77}{space 3} .2227947
{txt}{space 16}female {c |}{col 24}{res}{space 2}-.0298681{col 36}{space 2} .0288943{col 47}{space 1}   -1.03{col 56}{space 3}0.301{col 64}{space 4}-.0865512{col 77}{space 3}  .026815
{txt}{space 22} {c |}
{space 16}income {c |}
Menos o igual a 300 €  {c |}{col 24}{res}{space 2} .0181334{col 36}{space 2} .0936736{col 47}{space 1}    0.19{col 56}{space 3}0.847{col 64}{space 4}  -.16563{col 77}{space 3} .2018968
{txt}{space 7}De 301 a 600 €  {c |}{col 24}{res}{space 2}  .000288{col 36}{space 2}  .059473{col 47}{space 1}    0.00{col 56}{space 3}0.996{col 64}{space 4}-.1163826{col 77}{space 3} .1169586
{txt}{space 7}De 601 a 900 €  {c |}{col 24}{res}{space 2}-.0458199{col 36}{space 2} .0499288{col 47}{space 1}   -0.92{col 56}{space 3}0.359{col 64}{space 4}-.1437672{col 77}{space 3} .0521275
{txt}{space 5}De 901 a 1.200 €  {c |}{col 24}{res}{space 2} -.083785{col 36}{space 2} .0470618{col 47}{space 1}   -1.78{col 56}{space 3}0.075{col 64}{space 4}-.1761082{col 77}{space 3} .0085381
{txt}{space 3}De 1.201 a 1.800 €  {c |}{col 24}{res}{space 2}-.0991409{col 36}{space 2}  .049104{col 47}{space 1}   -2.02{col 56}{space 3}0.044{col 64}{space 4}-.1954702{col 77}{space 3}-.0028116
{txt}{space 3}De 1.801 a 2.400 €  {c |}{col 24}{res}{space 2}-.0589297{col 36}{space 2} .0604075{col 47}{space 1}   -0.98{col 56}{space 3}0.329{col 64}{space 4}-.1774336{col 77}{space 3} .0595743
{txt}{space 3}De 2.401 a 3.000 €  {c |}{col 24}{res}{space 2}-.2054812{col 36}{space 2} .0823241{col 47}{space 1}   -2.50{col 56}{space 3}0.013{col 64}{space 4}-.3669797{col 77}{space 3}-.0439827
{txt}{space 3}De 3.001 a 4.500 €  {c |}{col 24}{res}{space 2} .0670382{col 36}{space 2} .1111624{col 47}{space 1}    0.60{col 56}{space 3}0.547{col 64}{space 4}-.1510337{col 77}{space 3}   .28511
{txt}{space 3}De 4.501 a 6.000 €  {c |}{col 24}{res}{space 2}-.5142531{col 36}{space 2} .0520049{col 47}{space 1}   -9.89{col 56}{space 3}0.000{col 64}{space 4}-.6162732{col 77}{space 3} -.412233
{txt}{space 7}Más de 6.000 €  {c |}{col 24}{res}{space 2}-.0395171{col 36}{space 2} .2324089{col 47}{space 1}   -0.17{col 56}{space 3}0.865{col 64}{space 4}-.4954431{col 77}{space 3}  .416409
{txt}{space 22} {c |}
{space 19}age {c |}{col 24}{res}{space 2} .0040843{col 36}{space 2} .0048537{col 47}{space 1}    0.84{col 56}{space 3}0.400{col 64}{space 4}-.0054375{col 77}{space 3}  .013606
{txt}{space 16}age_sq {c |}{col 24}{res}{space 2}-.0000774{col 36}{space 2} .0000501{col 47}{space 1}   -1.54{col 56}{space 3}0.123{col 64}{space 4}-.0001757{col 77}{space 3}  .000021
{txt}{space 22} {c |}
{space 13}education {c |}
{space 13}Primaria  {c |}{col 24}{res}{space 2}-.0848678{col 36}{space 2} .1249759{col 47}{space 1}   -0.68{col 56}{space 3}0.497{col 64}{space 4}-.3300381{col 77}{space 3} .1603024
{txt}{space 2}Secundaria 1ª etapa  {c |}{col 24}{res}{space 2}-.2150703{col 36}{space 2} .1240375{col 47}{space 1}   -1.73{col 56}{space 3}0.083{col 64}{space 4}-.4583998{col 77}{space 3} .0282591
{txt}{space 2}Secundaria 2ª etapa  {c |}{col 24}{res}{space 2}-.2910842{col 36}{space 2} .1248737{col 47}{space 1}   -2.33{col 56}{space 3}0.020{col 64}{space 4}-.5360541{col 77}{space 3}-.0461144
{txt}{space 17}F.P.  {c |}{col 24}{res}{space 2}-.1822383{col 36}{space 2} .1247447{col 47}{space 1}   -1.46{col 56}{space 3}0.144{col 64}{space 4} -.426955{col 77}{space 3} .0624784
{txt}{space 11}Superiores  {c |}{col 24}{res}{space 2}-.2136564{col 36}{space 2} .1257698{col 47}{space 1}   -1.70{col 56}{space 3}0.090{col 64}{space 4}-.4603841{col 77}{space 3} .0330713
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} .7287888{col 36}{space 2} .1514973{col 47}{space 1}    4.81{col 56}{space 3}0.000{col 64}{space 4} .4315903{col 77}{space 3} 1.025987
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel ///
> (Removed, Mun Size, Model, cabine_use, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str8}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data.dta{rm}
saved
{p_end}

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured8_1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Fake model to start the data
. regr pp_dummy CCAA

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     3,376
{txt}{hline 13}{c +}{hline 34}   F(1, 3374)      = {res}     0.01
{txt}       Model {c |} {res} .001511648         1  .001511648   {txt}Prob > F        ={res}    0.9221
{txt}    Residual {c |} {res} 533.401332     3,374  .158091681   {txt}R-squared       ={res}    0.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}   -0.0003
{txt}       Total {c |} {res} 533.402844     3,375  .158045287   {txt}Root MSE        =   {res} .39761

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    pp_dummy{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}CCAA {c |}{col 14}{res}{space 2} .0001329{col 26}{space 2} .0013588{col 37}{space 1}    0.10{col 46}{space 3}0.922{col 54}{space 4}-.0025313{col 67}{space 3} .0027971
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .1955201{col 26}{space 2} .0137159{col 37}{space 1}   14.26{col 46}{space 3}0.000{col 54}{space 4} .1686279{col 67}{space 3} .2224123
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regsave CCAA using 01_data/survey_data_2.dta, ci level(95) replace addlabel ///
> (Removed, fake, Model, fake,  FE, fake)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. * Generate interaction
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
{txt}(2,957 missing values generated)

{com}. 
. * Actual analyses
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy i.income age age_sq i.education i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(44, 1311)       =  {res}     2.39
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0747
                                                {txt}Root MSE          =    {res} .27993

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0160757{col 45}{space 2} .0173974{col 56}{space 1}   -0.92{col 65}{space 3}0.356{col 73}{space 4}-.0502054{col 86}{space 3}  .018054
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0348437{col 45}{space 2} .0296604{col 56}{space 1}   -1.17{col 65}{space 3}0.240{col 73}{space 4}-.0930307{col 86}{space 3} .0233433
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1018081{col 45}{space 2} .0460283{col 56}{space 1}    2.21{col 65}{space 3}0.027{col 73}{space 4} .0115109{col 86}{space 3} .1921053
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0244379{col 45}{space 2} .0642031{col 56}{space 1}    0.38{col 65}{space 3}0.704{col 73}{space 4}-.1015141{col 86}{space 3}   .15039
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0761026{col 45}{space 2} .0408352{col 56}{space 1}    1.86{col 65}{space 3}0.063{col 73}{space 4} -.004007{col 86}{space 3} .1562122
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0045225{col 45}{space 2} .0306157{col 56}{space 1}    0.15{col 65}{space 3}0.883{col 73}{space 4}-.0555387{col 86}{space 3} .0645837
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0023769{col 45}{space 2} .0280213{col 56}{space 1}    0.08{col 65}{space 3}0.932{col 73}{space 4}-.0525945{col 86}{space 3} .0573483
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0079993{col 45}{space 2} .0278846{col 56}{space 1}   -0.29{col 65}{space 3}0.774{col 73}{space 4}-.0627027{col 86}{space 3} .0467041
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.055555{col 45}{space 2} .0301125{col 56}{space 1}   -1.84{col 65}{space 3}0.065{col 73}{space 4} -.114629{col 86}{space 3}  .003519
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0487728{col 45}{space 2} .0420429{col 56}{space 1}   -1.16{col 65}{space 3}0.246{col 73}{space 4}-.1312516{col 86}{space 3}  .033706
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0431181{col 45}{space 2} .0667544{col 56}{space 1}    0.65{col 65}{space 3}0.518{col 73}{space 4}-.0878389{col 86}{space 3} .1740751
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0901417{col 45}{space 2} .0415935{col 56}{space 1}   -2.17{col 65}{space 3}0.030{col 73}{space 4}-.1717388{col 86}{space 3}-.0085446
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0941105{col 45}{space 2} .0439658{col 56}{space 1}   -2.14{col 65}{space 3}0.032{col 73}{space 4}-.1803616{col 86}{space 3}-.0078595
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0004631{col 45}{space 2} .0031208{col 56}{space 1}   -0.15{col 65}{space 3}0.882{col 73}{space 4}-.0065855{col 86}{space 3} .0056592
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000103{col 45}{space 2} .0000331{col 56}{space 1}    0.31{col 65}{space 3}0.755{col 73}{space 4}-.0000545{col 86}{space 3} .0000752
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0846919{col 45}{space 2} .0917369{col 56}{space 1}   -0.92{col 65}{space 3}0.356{col 73}{space 4} -.264659{col 86}{space 3} .0952752
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0476901{col 45}{space 2} .0939749{col 56}{space 1}   -0.51{col 65}{space 3}0.612{col 73}{space 4}-.2320477{col 86}{space 3} .1366675
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0923449{col 45}{space 2} .0943915{col 56}{space 1}   -0.98{col 65}{space 3}0.328{col 73}{space 4}-.2775198{col 86}{space 3}   .09283
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} -.082031{col 45}{space 2} .0938693{col 56}{space 1}   -0.87{col 65}{space 3}0.382{col 73}{space 4}-.2661813{col 86}{space 3} .1021194
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0723339{col 45}{space 2}  .094541{col 56}{space 1}   -0.77{col 65}{space 3}0.444{col 73}{space 4}-.2578021{col 86}{space 3} .1131344
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .057631{col 45}{space 2} .0370509{col 56}{space 1}    1.56{col 65}{space 3}0.120{col 73}{space 4}-.0150546{col 86}{space 3} .1303166
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0210893{col 45}{space 2}  .032618{col 56}{space 1}    0.65{col 65}{space 3}0.518{col 73}{space 4}-.0428998{col 86}{space 3} .0850784
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0069832{col 45}{space 2} .0375698{col 56}{space 1}    0.19{col 65}{space 3}0.853{col 73}{space 4}-.0667204{col 86}{space 3} .0806868
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0055116{col 45}{space 2} .0337023{col 56}{space 1}   -0.16{col 65}{space 3}0.870{col 73}{space 4}-.0716279{col 86}{space 3} .0606047
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.038173{col 45}{space 2}  .036174{col 56}{space 1}   -1.06{col 65}{space 3}0.292{col 73}{space 4}-.1091382{col 86}{space 3} .0327922
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1006633{col 45}{space 2} .0428258{col 56}{space 1}   -2.35{col 65}{space 3}0.019{col 73}{space 4} -.184678{col 86}{space 3}-.0166487
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0182899{col 45}{space 2} .0360452{col 56}{space 1}   -0.51{col 65}{space 3}0.612{col 73}{space 4}-.0890024{col 86}{space 3} .0524226
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0557538{col 45}{space 2}  .054032{col 56}{space 1}    1.03{col 65}{space 3}0.302{col 73}{space 4}-.0502449{col 86}{space 3} .1617525
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0565928{col 45}{space 2} .0519132{col 56}{space 1}    1.09{col 65}{space 3}0.276{col 73}{space 4}-.0452493{col 86}{space 3} .1584349
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0587738{col 45}{space 2} .0344873{col 56}{space 1}   -1.70{col 65}{space 3}0.089{col 73}{space 4}  -.12643{col 86}{space 3} .0088825
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2} -.036857{col 45}{space 2} .0364185{col 56}{space 1}   -1.01{col 65}{space 3}0.312{col 73}{space 4}-.1083019{col 86}{space 3}  .034588
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1270295{col 45}{space 2} .0596927{col 56}{space 1}    2.13{col 65}{space 3}0.034{col 73}{space 4} .0099259{col 86}{space 3} .2441332
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0857479{col 45}{space 2} .0556374{col 56}{space 1}    1.54{col 65}{space 3}0.124{col 73}{space 4}-.0234001{col 86}{space 3} .1948959
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0105907{col 45}{space 2} .0350085{col 56}{space 1}    0.30{col 65}{space 3}0.762{col 73}{space 4}-.0580881{col 86}{space 3} .0792695
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0538111{col 45}{space 2}  .027652{col 56}{space 1}   -1.95{col 65}{space 3}0.052{col 73}{space 4}-.1080581{col 86}{space 3} .0004359
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0219642{col 45}{space 2} .0431505{col 56}{space 1}   -0.51{col 65}{space 3}0.611{col 73}{space 4}-.1066158{col 86}{space 3} .0626874
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0936278{col 45}{space 2}  .028606{col 56}{space 1}   -3.27{col 65}{space 3}0.001{col 73}{space 4}-.1497464{col 86}{space 3}-.0375092
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0968967{col 45}{space 2} .0415989{col 56}{space 1}    2.33{col 65}{space 3}0.020{col 73}{space 4}  .015289{col 86}{space 3} .1785043
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} -.063292{col 45}{space 2} .0247865{col 56}{space 1}   -2.55{col 65}{space 3}0.011{col 73}{space 4}-.1119175{col 86}{space 3}-.0146664
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0200074{col 45}{space 2} .0556981{col 56}{space 1}   -0.36{col 65}{space 3}0.719{col 73}{space 4}-.1292747{col 86}{space 3} .0892598
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.059788{col 45}{space 2} .0357435{col 56}{space 1}   -1.67{col 65}{space 3}0.095{col 73}{space 4}-.1299088{col 86}{space 3} .0103327
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0905551{col 45}{space 2} .0255838{col 56}{space 1}   -3.54{col 65}{space 3}0.000{col 73}{space 4}-.1407448{col 86}{space 3}-.0403655
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0942615{col 45}{space 2} .0816352{col 56}{space 1}    1.15{col 65}{space 3}0.248{col 73}{space 4}-.0658883{col 86}{space 3} .2544113
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} -.034456{col 45}{space 2} .0635353{col 56}{space 1}   -0.54{col 65}{space 3}0.588{col 73}{space 4}-.1590981{col 86}{space 3}  .090186
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1584068{col 45}{space 2} .1101955{col 56}{space 1}    1.44{col 65}{space 3}0.151{col 73}{space 4}-.0577721{col 86}{space 3} .3745856
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Female, Model, uncomfortable, FE, With region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female age age_sq i.education i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,845
                                                {txt}{help j_robustsingular:F(35, 1808) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0659
                                                {txt}Root MSE          =    {res} .29604

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}  -.02596{col 45}{space 2} .0166925{col 56}{space 1}   -1.56{col 65}{space 3}0.120{col 73}{space 4}-.0586987{col 86}{space 3} .0067787
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0321446{col 45}{space 2} .0268523{col 56}{space 1}   -1.20{col 65}{space 3}0.231{col 73}{space 4}-.0848094{col 86}{space 3} .0205203
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .0997502{col 45}{space 2}  .041755{col 56}{space 1}    2.39{col 65}{space 3}0.017{col 73}{space 4} .0178572{col 86}{space 3} .1816432
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0244014{col 45}{space 2}  .013965{col 56}{space 1}    1.75{col 65}{space 3}0.081{col 73}{space 4}-.0029877{col 86}{space 3} .0517905
{txt}{space 28}age {c |}{col 33}{res}{space 2} .0017546{col 45}{space 2} .0025987{col 56}{space 1}    0.68{col 65}{space 3}0.500{col 73}{space 4}-.0033421{col 86}{space 3} .0068514
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000189{col 45}{space 2} .0000281{col 56}{space 1}   -0.67{col 65}{space 3}0.501{col 73}{space 4} -.000074{col 86}{space 3} .0000362
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1559313{col 45}{space 2} .0792874{col 56}{space 1}   -1.97{col 65}{space 3}0.049{col 73}{space 4}-.3114358{col 86}{space 3}-.0004268
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1799854{col 45}{space 2} .0797898{col 56}{space 1}   -2.26{col 65}{space 3}0.024{col 73}{space 4}-.3364753{col 86}{space 3}-.0234955
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1991584{col 45}{space 2} .0800952{col 56}{space 1}   -2.49{col 65}{space 3}0.013{col 73}{space 4}-.3562473{col 86}{space 3}-.0420695
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1877586{col 45}{space 2} .0801219{col 56}{space 1}   -2.34{col 65}{space 3}0.019{col 73}{space 4}-.3448997{col 86}{space 3}-.0306174
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.2034999{col 45}{space 2} .0794906{col 56}{space 1}   -2.56{col 65}{space 3}0.011{col 73}{space 4}-.3594031{col 86}{space 3}-.0475968
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2} .7543421{col 45}{space 2} .0844704{col 56}{space 1}    8.93{col 65}{space 3}0.000{col 73}{space 4} .5886723{col 86}{space 3}  .920012
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0519357{col 45}{space 2} .0339977{col 56}{space 1}    1.53{col 65}{space 3}0.127{col 73}{space 4}-.0147431{col 86}{space 3} .1186145
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0332507{col 45}{space 2} .0299087{col 56}{space 1}    1.11{col 65}{space 3}0.266{col 73}{space 4}-.0254085{col 86}{space 3} .0919099
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0341557{col 45}{space 2} .0347578{col 56}{space 1}    0.98{col 65}{space 3}0.326{col 73}{space 4} -.034014{col 86}{space 3} .1023254
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0086743{col 45}{space 2} .0310895{col 56}{space 1}    0.28{col 65}{space 3}0.780{col 73}{space 4}-.0523008{col 86}{space 3} .0696493
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0335382{col 45}{space 2} .0326885{col 56}{space 1}   -1.03{col 65}{space 3}0.305{col 73}{space 4}-.0976495{col 86}{space 3}  .030573
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0816202{col 45}{space 2} .0362992{col 56}{space 1}   -2.25{col 65}{space 3}0.025{col 73}{space 4}-.1528129{col 86}{space 3}-.0104274
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} .0046845{col 45}{space 2} .0392841{col 56}{space 1}    0.12{col 65}{space 3}0.905{col 73}{space 4}-.0723624{col 86}{space 3} .0817314
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0869444{col 45}{space 2} .0560895{col 56}{space 1}    1.55{col 65}{space 3}0.121{col 73}{space 4}-.0230628{col 86}{space 3} .1969515
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0294812{col 45}{space 2} .0426592{col 56}{space 1}    0.69{col 65}{space 3}0.490{col 73}{space 4}-.0541854{col 86}{space 3} .1131478
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0674888{col 45}{space 2} .0354478{col 56}{space 1}   -1.90{col 65}{space 3}0.057{col 73}{space 4}-.1370117{col 86}{space 3}  .002034
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0269234{col 45}{space 2} .0386741{col 56}{space 1}   -0.70{col 65}{space 3}0.486{col 73}{space 4} -.102774{col 86}{space 3} .0489272
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1236697{col 45}{space 2} .0584612{col 56}{space 1}    2.12{col 65}{space 3}0.035{col 73}{space 4}  .009011{col 86}{space 3} .2383284
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0958419{col 45}{space 2}  .050632{col 56}{space 1}    1.89{col 65}{space 3}0.059{col 73}{space 4}-.0034614{col 86}{space 3} .1951453
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0403136{col 45}{space 2} .0282889{col 56}{space 1}   -1.43{col 65}{space 3}0.154{col 73}{space 4} -.095796{col 86}{space 3} .0151688
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0759636{col 45}{space 2} .0250698{col 56}{space 1}   -3.03{col 65}{space 3}0.002{col 73}{space 4}-.1251324{col 86}{space 3}-.0267948
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0248094{col 45}{space 2} .0404769{col 56}{space 1}   -0.61{col 65}{space 3}0.540{col 73}{space 4}-.1041959{col 86}{space 3}  .054577
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0574159{col 45}{space 2} .0344846{col 56}{space 1}   -1.66{col 65}{space 3}0.096{col 73}{space 4}-.1250498{col 86}{space 3}  .010218
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0469842{col 45}{space 2} .0363192{col 56}{space 1}    1.29{col 65}{space 3}0.196{col 73}{space 4}-.0242477{col 86}{space 3} .1182161
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0891789{col 45}{space 2} .0230362{col 56}{space 1}   -3.87{col 65}{space 3}0.000{col 73}{space 4}-.1343592{col 86}{space 3}-.0439985
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2} .0296059{col 45}{space 2} .0604033{col 56}{space 1}    0.49{col 65}{space 3}0.624{col 73}{space 4}-.0888618{col 86}{space 3} .1480736
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0757668{col 45}{space 2} .0323512{col 56}{space 1}   -2.34{col 65}{space 3}0.019{col 73}{space 4}-.1392164{col 86}{space 3}-.0123172
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0249346{col 45}{space 2} .0413643{col 56}{space 1}   -0.60{col 65}{space 3}0.547{col 73}{space 4}-.1060614{col 86}{space 3} .0561923
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0504117{col 45}{space 2} .0700348{col 56}{space 1}    0.72{col 65}{space 3}0.472{col 73}{space 4}-.0869459{col 86}{space 3} .1877694
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0710757{col 45}{space 2}  .065662{col 56}{space 1}   -1.08{col 65}{space 3}0.279{col 73}{space 4}-.1998571{col 86}{space 3} .0577057
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .2420786{col 45}{space 2} .0968857{col 56}{space 1}    2.50{col 65}{space 3}0.013{col 73}{space 4} .0520588{col 86}{space 3} .4320984
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Income, Model, uncomfortable, FE, With region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.education i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(43, 1312)       =  {res}     2.42
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0763
                                                {txt}Root MSE          =    {res} .27958

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0171238{col 45}{space 2} .0173984{col 56}{space 1}   -0.98{col 65}{space 3}0.325{col 73}{space 4}-.0512555{col 86}{space 3}  .017008
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0382663{col 45}{space 2} .0291772{col 56}{space 1}   -1.31{col 65}{space 3}0.190{col 73}{space 4}-.0955054{col 86}{space 3} .0189729
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1078883{col 45}{space 2} .0460072{col 56}{space 1}    2.35{col 65}{space 3}0.019{col 73}{space 4} .0176326{col 86}{space 3}  .198144
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0290755{col 45}{space 2} .0156643{col 56}{space 1}    1.86{col 65}{space 3}0.064{col 73}{space 4}-.0016542{col 86}{space 3} .0598052
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0257561{col 45}{space 2} .0635193{col 56}{space 1}    0.41{col 65}{space 3}0.685{col 73}{space 4}-.0988543{col 86}{space 3} .1503666
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0814072{col 45}{space 2} .0401394{col 56}{space 1}    2.03{col 65}{space 3}0.043{col 73}{space 4} .0026628{col 86}{space 3} .1601516
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0116792{col 45}{space 2} .0291994{col 56}{space 1}    0.40{col 65}{space 3}0.689{col 73}{space 4}-.0456033{col 86}{space 3} .0689617
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0119859{col 45}{space 2} .0255522{col 56}{space 1}    0.47{col 65}{space 3}0.639{col 73}{space 4}-.0381419{col 86}{space 3} .0621136
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0074195{col 45}{space 2} .0246294{col 56}{space 1}    0.30{col 65}{space 3}0.763{col 73}{space 4}-.0408978{col 86}{space 3} .0557367
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0345489{col 45}{space 2} .0259456{col 56}{space 1}   -1.33{col 65}{space 3}0.183{col 73}{space 4}-.0854483{col 86}{space 3} .0163504
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0234597{col 45}{space 2} .0378318{col 56}{space 1}   -0.62{col 65}{space 3}0.535{col 73}{space 4}-.0976773{col 86}{space 3} .0507578
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0631557{col 45}{space 2} .0661511{col 56}{space 1}    0.95{col 65}{space 3}0.340{col 73}{space 4}-.0666177{col 86}{space 3} .1929291
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0752633{col 45}{space 2} .0467788{col 56}{space 1}   -1.61{col 65}{space 3}0.108{col 73}{space 4}-.1670327{col 86}{space 3} .0165062
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0686962{col 45}{space 2}  .040677{col 56}{space 1}   -1.69{col 65}{space 3}0.091{col 73}{space 4}-.1484952{col 86}{space 3} .0111029
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0879912{col 45}{space 2} .0913813{col 56}{space 1}   -0.96{col 65}{space 3}0.336{col 73}{space 4}-.2672607{col 86}{space 3} .0912783
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0613412{col 45}{space 2} .0915489{col 56}{space 1}   -0.67{col 65}{space 3}0.503{col 73}{space 4}-.2409394{col 86}{space 3}  .118257
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1086507{col 45}{space 2} .0916907{col 56}{space 1}   -1.18{col 65}{space 3}0.236{col 73}{space 4}-.2885272{col 86}{space 3} .0712257
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0997864{col 45}{space 2} .0908392{col 56}{space 1}   -1.10{col 65}{space 3}0.272{col 73}{space 4}-.2779923{col 86}{space 3} .0784195
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0948682{col 45}{space 2} .0917026{col 56}{space 1}   -1.03{col 65}{space 3}0.301{col 73}{space 4}-.2747679{col 86}{space 3} .0850315
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0541246{col 45}{space 2} .0368802{col 56}{space 1}    1.47{col 65}{space 3}0.142{col 73}{space 4}-.0182261{col 86}{space 3} .1264752
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}  .019289{col 45}{space 2} .0322746{col 56}{space 1}    0.60{col 65}{space 3}0.550{col 73}{space 4}-.0440265{col 86}{space 3} .0826045
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0052083{col 45}{space 2} .0375743{col 56}{space 1}    0.14{col 65}{space 3}0.890{col 73}{space 4}-.0685039{col 86}{space 3} .0789205
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0070772{col 45}{space 2} .0337276{col 56}{space 1}   -0.21{col 65}{space 3}0.834{col 73}{space 4}-.0732431{col 86}{space 3} .0590886
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0377464{col 45}{space 2} .0357858{col 56}{space 1}   -1.05{col 65}{space 3}0.292{col 73}{space 4}  -.10795{col 86}{space 3} .0324572
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1036478{col 45}{space 2} .0421054{col 56}{space 1}   -2.46{col 65}{space 3}0.014{col 73}{space 4}-.1862491{col 86}{space 3}-.0210465
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} -.021064{col 45}{space 2} .0353831{col 56}{space 1}   -0.60{col 65}{space 3}0.552{col 73}{space 4}-.0904775{col 86}{space 3} .0483496
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0560403{col 45}{space 2}  .054163{col 56}{space 1}    1.03{col 65}{space 3}0.301{col 73}{space 4}-.0502153{col 86}{space 3} .1622959
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0524065{col 45}{space 2} .0516936{col 56}{space 1}    1.01{col 65}{space 3}0.311{col 73}{space 4}-.0490046{col 86}{space 3} .1538175
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0630433{col 45}{space 2} .0343871{col 56}{space 1}   -1.83{col 65}{space 3}0.067{col 73}{space 4}-.1305029{col 86}{space 3} .0044163
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0339612{col 45}{space 2}  .036313{col 56}{space 1}   -0.94{col 65}{space 3}0.350{col 73}{space 4}-.1051991{col 86}{space 3} .0372768
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1272402{col 45}{space 2} .0595519{col 56}{space 1}    2.14{col 65}{space 3}0.033{col 73}{space 4} .0104128{col 86}{space 3} .2440676
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0865629{col 45}{space 2} .0550842{col 56}{space 1}    1.57{col 65}{space 3}0.116{col 73}{space 4}-.0214999{col 86}{space 3} .1946257
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0096528{col 45}{space 2} .0353444{col 56}{space 1}    0.27{col 65}{space 3}0.785{col 73}{space 4} -.059685{col 86}{space 3} .0789906
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0535107{col 45}{space 2} .0273373{col 56}{space 1}   -1.96{col 65}{space 3}0.051{col 73}{space 4}-.1071404{col 86}{space 3}  .000119
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0204161{col 45}{space 2} .0432372{col 56}{space 1}   -0.47{col 65}{space 3}0.637{col 73}{space 4}-.1052377{col 86}{space 3} .0644056
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0907454{col 45}{space 2} .0279328{col 56}{space 1}   -3.25{col 65}{space 3}0.001{col 73}{space 4}-.1455432{col 86}{space 3}-.0359476
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0986689{col 45}{space 2} .0413767{col 56}{space 1}    2.38{col 65}{space 3}0.017{col 73}{space 4} .0174972{col 86}{space 3} .1798407
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0642349{col 45}{space 2} .0246997{col 56}{space 1}   -2.60{col 65}{space 3}0.009{col 73}{space 4}-.1126902{col 86}{space 3}-.0157796
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0140547{col 45}{space 2} .0555841{col 56}{space 1}   -0.25{col 65}{space 3}0.800{col 73}{space 4}-.1230981{col 86}{space 3} .0949887
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0579101{col 45}{space 2}  .035502{col 56}{space 1}   -1.63{col 65}{space 3}0.103{col 73}{space 4}-.1275569{col 86}{space 3} .0117367
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0900179{col 45}{space 2} .0255234{col 56}{space 1}   -3.53{col 65}{space 3}0.000{col 73}{space 4} -.140089{col 86}{space 3}-.0399469
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0966838{col 45}{space 2} .0806248{col 56}{space 1}    1.20{col 65}{space 3}0.231{col 73}{space 4}-.0614839{col 86}{space 3} .2548514
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0332477{col 45}{space 2} .0640349{col 56}{space 1}   -0.52{col 65}{space 3}0.604{col 73}{space 4}-.1588697{col 86}{space 3} .0923742
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1548695{col 45}{space 2} .0964842{col 56}{space 1}    1.61{col 65}{space 3}0.109{col 73}{space 4}-.0344107{col 86}{space 3} .3441497
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Age and age squared, Model, uncomfortable, FE, With region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income age age_sq i.TAMUNI i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,357
                                                {txt}F(40, 1316)       =  {res}     2.62
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0727
                                                {txt}Root MSE          =    {res} .27971

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0148612{col 45}{space 2} .0173116{col 56}{space 1}   -0.86{col 65}{space 3}0.391{col 73}{space 4}-.0488225{col 86}{space 3} .0191001
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0373887{col 45}{space 2} .0297172{col 56}{space 1}   -1.26{col 65}{space 3}0.209{col 73}{space 4}-.0956871{col 86}{space 3} .0209096
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1023232{col 45}{space 2} .0459078{col 56}{space 1}    2.23{col 65}{space 3}0.026{col 73}{space 4} .0122627{col 86}{space 3} .1923836
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0275267{col 45}{space 2} .0155344{col 56}{space 1}    1.77{col 65}{space 3}0.077{col 73}{space 4}-.0029483{col 86}{space 3} .0580016
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0287215{col 45}{space 2} .0631973{col 56}{space 1}    0.45{col 65}{space 3}0.650{col 73}{space 4} -.095257{col 86}{space 3}    .1527
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0805202{col 45}{space 2} .0408338{col 56}{space 1}    1.97{col 65}{space 3}0.049{col 73}{space 4} .0004138{col 86}{space 3} .1606266
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0115008{col 45}{space 2}  .029934{col 56}{space 1}    0.38{col 65}{space 3}0.701{col 73}{space 4}-.0472229{col 86}{space 3} .0702244
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0123277{col 45}{space 2} .0283916{col 56}{space 1}    0.43{col 65}{space 3}0.664{col 73}{space 4}-.0433701{col 86}{space 3} .0680255
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0030491{col 45}{space 2} .0279887{col 56}{space 1}    0.11{col 65}{space 3}0.913{col 73}{space 4}-.0518582{col 86}{space 3} .0579565
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0451732{col 45}{space 2} .0280957{col 56}{space 1}   -1.61{col 65}{space 3}0.108{col 73}{space 4}-.1002905{col 86}{space 3}  .009944
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0331929{col 45}{space 2} .0404812{col 56}{space 1}   -0.82{col 65}{space 3}0.412{col 73}{space 4}-.1126076{col 86}{space 3} .0462219
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0577207{col 45}{space 2} .0657477{col 56}{space 1}    0.88{col 65}{space 3}0.380{col 73}{space 4} -.071261{col 86}{space 3} .1867024
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.083732{col 45}{space 2} .0423313{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4}-.1667762{col 86}{space 3}-.0006879
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.082443{col 45}{space 2} .0400923{col 56}{space 1}   -2.06{col 65}{space 3}0.040{col 73}{space 4}-.1610948{col 86}{space 3}-.0037913
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0007594{col 45}{space 2} .0030641{col 56}{space 1}   -0.25{col 65}{space 3}0.804{col 73}{space 4}-.0067705{col 86}{space 3} .0052517
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000143{col 45}{space 2} .0000317{col 56}{space 1}    0.45{col 65}{space 3}0.653{col 73}{space 4}-.0000479{col 86}{space 3} .0000764
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0533775{col 45}{space 2} .0372372{col 56}{space 1}    1.43{col 65}{space 3}0.152{col 73}{space 4}-.0196733{col 86}{space 3} .1264283
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}  .020365{col 45}{space 2}  .033162{col 56}{space 1}    0.61{col 65}{space 3}0.539{col 73}{space 4}-.0446912{col 86}{space 3} .0854211
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0012267{col 45}{space 2} .0378852{col 56}{space 1}    0.03{col 65}{space 3}0.974{col 73}{space 4}-.0730952{col 86}{space 3} .0755486
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0091166{col 45}{space 2} .0338217{col 56}{space 1}   -0.27{col 65}{space 3}0.788{col 73}{space 4}-.0754669{col 86}{space 3} .0572338
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0444173{col 45}{space 2} .0360444{col 56}{space 1}   -1.23{col 65}{space 3}0.218{col 73}{space 4}-.1151281{col 86}{space 3} .0262936
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.103267{col 45}{space 2} .0422757{col 56}{space 1}   -2.44{col 65}{space 3}0.015{col 73}{space 4}-.1862022{col 86}{space 3}-.0203319
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0278589{col 45}{space 2} .0353843{col 56}{space 1}   -0.79{col 65}{space 3}0.431{col 73}{space 4}-.0972747{col 86}{space 3}  .041557
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0538211{col 45}{space 2} .0546345{col 56}{space 1}    0.99{col 65}{space 3}0.325{col 73}{space 4}-.0533591{col 86}{space 3} .1610013
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0494898{col 45}{space 2} .0515622{col 56}{space 1}    0.96{col 65}{space 3}0.337{col 73}{space 4}-.0516632{col 86}{space 3} .1506429
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} -.069039{col 45}{space 2} .0341656{col 56}{space 1}   -2.02{col 65}{space 3}0.044{col 73}{space 4}-.1360641{col 86}{space 3}-.0020139
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0431382{col 45}{space 2}  .036654{col 56}{space 1}   -1.18{col 65}{space 3}0.239{col 73}{space 4}-.1150448{col 86}{space 3} .0287684
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1220683{col 45}{space 2}   .05893{col 56}{space 1}    2.07{col 65}{space 3}0.039{col 73}{space 4} .0064613{col 86}{space 3} .2376752
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}  .076623{col 45}{space 2} .0554462{col 56}{space 1}    1.38{col 65}{space 3}0.167{col 73}{space 4}-.0321496{col 86}{space 3} .1853956
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0050742{col 45}{space 2}  .035092{col 56}{space 1}    0.14{col 65}{space 3}0.885{col 73}{space 4} -.063768{col 86}{space 3} .0739165
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0583847{col 45}{space 2} .0272144{col 56}{space 1}   -2.15{col 65}{space 3}0.032{col 73}{space 4}-.1117729{col 86}{space 3}-.0049964
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0227128{col 45}{space 2} .0428016{col 56}{space 1}   -0.53{col 65}{space 3}0.596{col 73}{space 4}-.1066795{col 86}{space 3}  .061254
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0982743{col 45}{space 2} .0284998{col 56}{space 1}   -3.45{col 65}{space 3}0.001{col 73}{space 4}-.1541843{col 86}{space 3}-.0423642
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0904505{col 45}{space 2} .0413352{col 56}{space 1}    2.19{col 65}{space 3}0.029{col 73}{space 4} .0093604{col 86}{space 3} .1715407
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0673089{col 45}{space 2} .0247001{col 56}{space 1}   -2.73{col 65}{space 3}0.007{col 73}{space 4}-.1157648{col 86}{space 3}-.0188531
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0218557{col 45}{space 2} .0552232{col 56}{space 1}   -0.40{col 65}{space 3}0.692{col 73}{space 4}-.1301909{col 86}{space 3} .0864795
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.066178{col 45}{space 2} .0348013{col 56}{space 1}   -1.90{col 65}{space 3}0.057{col 73}{space 4}-.1344501{col 86}{space 3} .0020941
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0962578{col 45}{space 2} .0249472{col 56}{space 1}   -3.86{col 65}{space 3}0.000{col 73}{space 4}-.1451984{col 86}{space 3}-.0473173
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0962133{col 45}{space 2} .0810814{col 56}{space 1}    1.19{col 65}{space 3}0.236{col 73}{space 4}-.0628495{col 86}{space 3} .2552762
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0347795{col 45}{space 2} .0634464{col 56}{space 1}   -0.55{col 65}{space 3}0.584{col 73}{space 4}-.1592467{col 86}{space 3} .0896877
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .0760915{col 45}{space 2} .0753512{col 56}{space 1}    1.01{col 65}{space 3}0.313{col 73}{space 4}  -.07173{col 86}{space 3} .2239131
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Education, Model, uncomfortable, FE, With region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str9}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income age age_sq i.education i.CCAA, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(39, 1316)       =  {res}     2.71
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0634
                                                {txt}Root MSE          =    {res} .28109

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                uncomfortable{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}cabine_use {c |}{col 31}{res}{space 2}-.0046278{col 43}{space 2}  .017142{col 54}{space 1}   -0.27{col 63}{space 3}0.787{col 71}{space 4}-.0382565{col 84}{space 3} .0290009
{txt}{space 21}pp_dummy {c |}{col 31}{res}{space 2}-.0468004{col 43}{space 2} .0303969{col 54}{space 1}   -1.54{col 63}{space 3}0.124{col 71}{space 4}-.1064321{col 84}{space 3} .0128313
{txt}{space 10}cabine_use_pp_dummy {c |}{col 31}{res}{space 2}  .117398{col 43}{space 2} .0461072{col 54}{space 1}    2.55{col 63}{space 3}0.011{col 71}{space 4} .0269463{col 84}{space 3} .2078496
{txt}{space 23}female {c |}{col 31}{res}{space 2} .0284169{col 43}{space 2} .0158636{col 54}{space 1}    1.79{col 63}{space 3}0.073{col 71}{space 4}-.0027038{col 84}{space 3} .0595377
{txt}{space 29} {c |}
{space 23}income {c |}
{space 7}Menos o igual a 300 €  {c |}{col 31}{res}{space 2} .0221153{col 43}{space 2} .0643666{col 54}{space 1}    0.34{col 63}{space 3}0.731{col 71}{space 4} -.104157{col 84}{space 3} .1483875
{txt}{space 14}De 301 a 600 €  {c |}{col 31}{res}{space 2} .0819267{col 43}{space 2} .0410386{col 54}{space 1}    2.00{col 63}{space 3}0.046{col 71}{space 4} .0014185{col 84}{space 3}  .162435
{txt}{space 14}De 601 a 900 €  {c |}{col 31}{res}{space 2} .0068138{col 43}{space 2} .0305488{col 54}{space 1}    0.22{col 63}{space 3}0.824{col 71}{space 4} -.053116{col 84}{space 3} .0667435
{txt}{space 12}De 901 a 1.200 €  {c |}{col 31}{res}{space 2} .0078883{col 43}{space 2} .0283493{col 54}{space 1}    0.28{col 63}{space 3}0.781{col 71}{space 4}-.0477264{col 84}{space 3}  .063503
{txt}{space 10}De 1.201 a 1.800 €  {c |}{col 31}{res}{space 2} .0018073{col 43}{space 2} .0281908{col 54}{space 1}    0.06{col 63}{space 3}0.949{col 71}{space 4}-.0534964{col 84}{space 3} .0571111
{txt}{space 10}De 1.801 a 2.400 €  {c |}{col 31}{res}{space 2}-.0354991{col 43}{space 2} .0303806{col 54}{space 1}   -1.17{col 63}{space 3}0.243{col 71}{space 4}-.0950987{col 84}{space 3} .0241006
{txt}{space 10}De 2.401 a 3.000 €  {c |}{col 31}{res}{space 2}-.0374976{col 43}{space 2} .0430184{col 54}{space 1}   -0.87{col 63}{space 3}0.384{col 71}{space 4}-.1218897{col 84}{space 3} .0468945
{txt}{space 10}De 3.001 a 4.500 €  {c |}{col 31}{res}{space 2} .0552316{col 43}{space 2} .0699756{col 54}{space 1}    0.79{col 63}{space 3}0.430{col 71}{space 4}-.0820443{col 84}{space 3} .1925075
{txt}{space 10}De 4.501 a 6.000 €  {c |}{col 31}{res}{space 2}-.0609208{col 43}{space 2} .0386488{col 54}{space 1}   -1.58{col 63}{space 3}0.115{col 71}{space 4}-.1367408{col 84}{space 3} .0148991
{txt}{space 14}Más de 6.000 €  {c |}{col 31}{res}{space 2}-.0513082{col 43}{space 2} .0329827{col 54}{space 1}   -1.56{col 63}{space 3}0.120{col 71}{space 4}-.1160126{col 84}{space 3} .0133961
{txt}{space 29} {c |}
{space 26}age {c |}{col 31}{res}{space 2}-.0014073{col 43}{space 2} .0031425{col 54}{space 1}   -0.45{col 63}{space 3}0.654{col 71}{space 4}-.0075721{col 84}{space 3} .0047576
{txt}{space 23}age_sq {c |}{col 31}{res}{space 2} .0000163{col 43}{space 2} .0000333{col 54}{space 1}    0.49{col 63}{space 3}0.625{col 71}{space 4}-.0000491{col 84}{space 3} .0000817
{txt}{space 29} {c |}
{space 20}education {c |}
{space 20}Primaria  {c |}{col 31}{res}{space 2}-.0851615{col 43}{space 2} .0917651{col 54}{space 1}   -0.93{col 63}{space 3}0.354{col 71}{space 4}-.2651834{col 84}{space 3} .0948603
{txt}{space 9}Secundaria 1ª etapa  {c |}{col 31}{res}{space 2} -.048432{col 43}{space 2} .0937855{col 54}{space 1}   -0.52{col 63}{space 3}0.606{col 71}{space 4}-.2324174{col 84}{space 3} .1355533
{txt}{space 9}Secundaria 2ª etapa  {c |}{col 31}{res}{space 2} -.095617{col 43}{space 2} .0938743{col 54}{space 1}   -1.02{col 63}{space 3}0.309{col 71}{space 4}-.2797765{col 84}{space 3} .0885426
{txt}{space 24}F.P.  {c |}{col 31}{res}{space 2}-.0879323{col 43}{space 2}  .093448{col 54}{space 1}   -0.94{col 63}{space 3}0.347{col 71}{space 4}-.2712557{col 84}{space 3} .0953911
{txt}{space 18}Superiores  {c |}{col 31}{res}{space 2}-.0886979{col 43}{space 2} .0939451{col 54}{space 1}   -0.94{col 63}{space 3}0.345{col 71}{space 4}-.2729965{col 84}{space 3} .0956007
{txt}{space 29} {c |}
{space 25}CCAA {c |}
{space 22}Aragón  {c |}{col 31}{res}{space 2}-.0358066{col 43}{space 2} .0356851{col 54}{space 1}   -1.00{col 63}{space 3}0.316{col 71}{space 4}-.1058124{col 84}{space 3} .0341992
{txt}{space 4}Asturias (Principado de)  {c |}{col 31}{res}{space 2} .0571556{col 43}{space 2} .0529941{col 54}{space 1}    1.08{col 63}{space 3}0.281{col 71}{space 4}-.0468066{col 84}{space 3} .1611177
{txt}{space 13}Balears (Illes)  {c |}{col 31}{res}{space 2} .0423877{col 43}{space 2} .0506476{col 54}{space 1}    0.84{col 63}{space 3}0.403{col 71}{space 4}-.0569712{col 84}{space 3} .1417465
{txt}{space 20}Canarias  {c |}{col 31}{res}{space 2}-.0666758{col 43}{space 2} .0334143{col 54}{space 1}   -2.00{col 63}{space 3}0.046{col 71}{space 4}-.1322269{col 84}{space 3}-.0011246
{txt}{space 19}Cantabria  {c |}{col 31}{res}{space 2} -.020706{col 43}{space 2} .0347234{col 54}{space 1}   -0.60{col 63}{space 3}0.551{col 71}{space 4}-.0888253{col 84}{space 3} .0474134
{txt}{space 10}Castilla-La Mancha  {c |}{col 31}{res}{space 2} .1367653{col 43}{space 2} .0589115{col 54}{space 1}    2.32{col 63}{space 3}0.020{col 71}{space 4} .0211946{col 84}{space 3}  .252336
{txt}{space 13}Castilla y León  {c |}{col 31}{res}{space 2}  .089748{col 43}{space 2} .0550609{col 54}{space 1}    1.63{col 63}{space 3}0.103{col 71}{space 4}-.0182686{col 84}{space 3} .1977647
{txt}{space 20}Cataluña  {c |}{col 31}{res}{space 2}-.0095527{col 43}{space 2} .0314368{col 54}{space 1}   -0.30{col 63}{space 3}0.761{col 71}{space 4}-.0712245{col 84}{space 3} .0521191
{txt}{space 8}Comunitat Valenciana  {c |}{col 31}{res}{space 2}-.0533871{col 43}{space 2}  .027254{col 54}{space 1}   -1.96{col 63}{space 3}0.050{col 71}{space 4}-.1068531{col 84}{space 3} .0000789
{txt}{space 17}Extremadura  {c |}{col 31}{res}{space 2}-.0149694{col 43}{space 2} .0426013{col 54}{space 1}   -0.35{col 63}{space 3}0.725{col 71}{space 4}-.0985433{col 84}{space 3} .0686046
{txt}{space 21}Galicia  {c |}{col 31}{res}{space 2}-.0780152{col 43}{space 2} .0264908{col 54}{space 1}   -2.94{col 63}{space 3}0.003{col 71}{space 4} -.129984{col 84}{space 3}-.0260465
{txt}{space 7}Madrid (Comunidad de)  {c |}{col 31}{res}{space 2} .0688537{col 43}{space 2} .0359927{col 54}{space 1}    1.91{col 63}{space 3}0.056{col 71}{space 4}-.0017555{col 84}{space 3}  .139463
{txt}{space 10}Murcia (Región de)  {c |}{col 31}{res}{space 2}-.0750808{col 43}{space 2} .0251553{col 54}{space 1}   -2.98{col 63}{space 3}0.003{col 71}{space 4}-.1244297{col 84}{space 3}-.0257319
{txt}Navarra (Comunidad Foral de)  {c |}{col 31}{res}{space 2} .0079504{col 43}{space 2} .0539997{col 54}{space 1}    0.15{col 63}{space 3}0.883{col 71}{space 4}-.0979844{col 84}{space 3} .1138853
{txt}{space 18}País Vasco  {c |}{col 31}{res}{space 2}-.0542921{col 43}{space 2} .0351403{col 54}{space 1}   -1.55{col 63}{space 3}0.123{col 71}{space 4}-.1232292{col 84}{space 3}  .014645
{txt}{space 18}Rioja (La)  {c |}{col 31}{res}{space 2}-.0914643{col 43}{space 2} .0228617{col 54}{space 1}   -4.00{col 63}{space 3}0.000{col 71}{space 4}-.1363136{col 84}{space 3} -.046615
{txt}{space 2}Ceuta (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2} .0865314{col 43}{space 2} .0781882{col 54}{space 1}    1.11{col 63}{space 3}0.269{col 71}{space 4}-.0668557{col 84}{space 3} .2399186
{txt}Melilla (Ciudad Autónoma de)  {c |}{col 31}{res}{space 2}-.0386532{col 43}{space 2} .0611644{col 54}{space 1}   -0.63{col 63}{space 3}0.528{col 71}{space 4}-.1586435{col 84}{space 3} .0813371
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .1760432{col 43}{space 2} .1064255{col 54}{space 1}    1.65{col 63}{space 3}0.098{col 71}{space 4}-.0327391{col 84}{space 3} .3848254
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Mun Size, Model, uncomfortable, FE, With region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str8}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy i.income age age_sq i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(26, 1329)       =  {res}     4.89
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0345
                                                {txt}Root MSE          =    {res} .28401

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0335483{col 45}{space 2} .0167101{col 56}{space 1}   -2.01{col 65}{space 3}0.045{col 73}{space 4}-.0663293{col 86}{space 3}-.0007673
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2} -.032705{col 45}{space 2} .0298347{col 56}{space 1}   -1.10{col 65}{space 3}0.273{col 73}{space 4}-.0912333{col 86}{space 3} .0258233
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1125013{col 45}{space 2} .0480388{col 56}{space 1}    2.34{col 65}{space 3}0.019{col 73}{space 4} .0182611{col 86}{space 3} .2067415
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0292243{col 45}{space 2} .0640083{col 56}{space 1}    0.46{col 65}{space 3}0.648{col 73}{space 4}-.0963439{col 86}{space 3} .1547925
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0631157{col 45}{space 2} .0416106{col 56}{space 1}    1.52{col 65}{space 3}0.130{col 73}{space 4}-.0185138{col 86}{space 3} .1447453
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0005856{col 45}{space 2} .0309611{col 56}{space 1}    0.02{col 65}{space 3}0.985{col 73}{space 4}-.0601524{col 86}{space 3} .0613235
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0048339{col 45}{space 2} .0290146{col 56}{space 1}    0.17{col 65}{space 3}0.868{col 73}{space 4}-.0520856{col 86}{space 3} .0617533
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0026074{col 45}{space 2} .0277713{col 56}{space 1}   -0.09{col 65}{space 3}0.925{col 73}{space 4}-.0570878{col 86}{space 3}  .051873
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0544109{col 45}{space 2} .0294214{col 56}{space 1}   -1.85{col 65}{space 3}0.065{col 73}{space 4}-.1121283{col 86}{space 3} .0033064
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0371614{col 45}{space 2} .0423932{col 56}{space 1}   -0.88{col 65}{space 3}0.381{col 73}{space 4}-.1203264{col 86}{space 3} .0460035
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0480765{col 45}{space 2} .0703213{col 56}{space 1}    0.68{col 65}{space 3}0.494{col 73}{space 4}-.0898763{col 86}{space 3} .1860293
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0984699{col 45}{space 2} .0310148{col 56}{space 1}   -3.17{col 65}{space 3}0.002{col 73}{space 4}-.1593132{col 86}{space 3}-.0376267
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0918733{col 45}{space 2}  .034138{col 56}{space 1}   -2.69{col 65}{space 3}0.007{col 73}{space 4}-.1588434{col 86}{space 3}-.0249031
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0014949{col 45}{space 2}  .003149{col 56}{space 1}   -0.47{col 65}{space 3}0.635{col 73}{space 4}-.0076723{col 86}{space 3} .0046826
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000197{col 45}{space 2} .0000333{col 56}{space 1}    0.59{col 65}{space 3}0.555{col 73}{space 4}-.0000457{col 86}{space 3}  .000085
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0908718{col 45}{space 2} .0899843{col 56}{space 1}   -1.01{col 65}{space 3}0.313{col 73}{space 4}-.2673985{col 86}{space 3} .0856549
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} -.055418{col 45}{space 2}  .091148{col 56}{space 1}   -0.61{col 65}{space 3}0.543{col 73}{space 4}-.2342277{col 86}{space 3} .1233916
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0999778{col 45}{space 2} .0915458{col 56}{space 1}   -1.09{col 65}{space 3}0.275{col 73}{space 4}-.2795678{col 86}{space 3} .0796121
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0925209{col 45}{space 2} .0911118{col 56}{space 1}   -1.02{col 65}{space 3}0.310{col 73}{space 4}-.2712596{col 86}{space 3} .0862178
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0820517{col 45}{space 2} .0915368{col 56}{space 1}   -0.90{col 65}{space 3}0.370{col 73}{space 4}-.2616241{col 86}{space 3} .0975208
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0625432{col 45}{space 2} .0376296{col 56}{space 1}    1.66{col 65}{space 3}0.097{col 73}{space 4}-.0112767{col 86}{space 3}  .136363
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0189713{col 45}{space 2} .0325457{col 56}{space 1}    0.58{col 65}{space 3}0.560{col 73}{space 4}-.0448753{col 86}{space 3} .0828178
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0379784{col 45}{space 2} .0365266{col 56}{space 1}    1.04{col 65}{space 3}0.299{col 73}{space 4}-.0336776{col 86}{space 3} .1096344
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0055404{col 45}{space 2} .0327895{col 56}{space 1}    0.17{col 65}{space 3}0.866{col 73}{space 4}-.0587844{col 86}{space 3} .0698651
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0481135{col 45}{space 2} .0323246{col 56}{space 1}   -1.49{col 65}{space 3}0.137{col 73}{space 4}-.1115263{col 86}{space 3} .0152994
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0417802{col 45}{space 2}  .036328{col 56}{space 1}   -1.15{col 65}{space 3}0.250{col 73}{space 4}-.1130467{col 86}{space 3} .0294863
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1931122{col 45}{space 2} .1070824{col 56}{space 1}    1.80{col 65}{space 3}0.072{col 73}{space 4}-.0169568{col 86}{space 3} .4031811
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Female, Model, uncomfortable, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str6}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female age age_sq i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,845
                                                {txt}{help j_robustsingular:F(17, 1826) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0343
                                                {txt}Root MSE          =    {res} .29953

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0295945{col 45}{space 2} .0154625{col 56}{space 1}   -1.91{col 65}{space 3}0.056{col 73}{space 4}-.0599206{col 86}{space 3} .0007316
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0179845{col 45}{space 2} .0266268{col 56}{space 1}   -0.68{col 65}{space 3}0.499{col 73}{space 4}-.0702067{col 86}{space 3} .0342378
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .0952435{col 45}{space 2} .0426052{col 56}{space 1}    2.24{col 65}{space 3}0.026{col 73}{space 4} .0116835{col 86}{space 3} .1788035
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0226491{col 45}{space 2} .0142247{col 56}{space 1}    1.59{col 65}{space 3}0.112{col 73}{space 4}-.0052493{col 86}{space 3} .0505474
{txt}{space 28}age {c |}{col 33}{res}{space 2} .0016713{col 45}{space 2} .0025975{col 56}{space 1}    0.64{col 65}{space 3}0.520{col 73}{space 4}-.0034231{col 86}{space 3} .0067657
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000195{col 45}{space 2}  .000028{col 56}{space 1}   -0.70{col 65}{space 3}0.486{col 73}{space 4}-.0000744{col 86}{space 3} .0000354
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1621373{col 45}{space 2} .0793387{col 56}{space 1}   -2.04{col 65}{space 3}0.041{col 73}{space 4}-.3177415{col 86}{space 3}-.0065332
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1912991{col 45}{space 2} .0786957{col 56}{space 1}   -2.43{col 65}{space 3}0.015{col 73}{space 4}-.3456422{col 86}{space 3} -.036956
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2090412{col 45}{space 2} .0790242{col 56}{space 1}   -2.65{col 65}{space 3}0.008{col 73}{space 4}-.3640285{col 86}{space 3}-.0540538
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} -.201864{col 45}{space 2} .0790355{col 56}{space 1}   -2.55{col 65}{space 3}0.011{col 73}{space 4}-.3568735{col 86}{space 3}-.0468545
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.2133883{col 45}{space 2} .0784253{col 56}{space 1}   -2.72{col 65}{space 3}0.007{col 73}{space 4}-.3672011{col 86}{space 3}-.0595756
{txt}{space 25}Otros  {c |}{col 33}{res}{space 2} .6955513{col 45}{space 2} .0788611{col 56}{space 1}    8.82{col 65}{space 3}0.000{col 73}{space 4} .5408838{col 86}{space 3} .8502188
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0456746{col 45}{space 2} .0344501{col 56}{space 1}    1.33{col 65}{space 3}0.185{col 73}{space 4}-.0218911{col 86}{space 3} .1132403
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0162852{col 45}{space 2} .0300945{col 56}{space 1}    0.54{col 65}{space 3}0.588{col 73}{space 4}-.0427381{col 86}{space 3} .0753084
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0407846{col 45}{space 2} .0342481{col 56}{space 1}    1.19{col 65}{space 3}0.234{col 73}{space 4}-.0263851{col 86}{space 3} .1079542
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0013441{col 45}{space 2}  .030581{col 56}{space 1}    0.04{col 65}{space 3}0.965{col 73}{space 4}-.0586332{col 86}{space 3} .0613215
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0537974{col 45}{space 2} .0307416{col 56}{space 1}   -1.75{col 65}{space 3}0.080{col 73}{space 4}-.1140897{col 86}{space 3}  .006495
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0690306{col 45}{space 2} .0311348{col 56}{space 1}   -2.22{col 65}{space 3}0.027{col 73}{space 4}-.1300942{col 86}{space 3} -.007967
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .2597643{col 45}{space 2} .0950502{col 56}{space 1}    2.73{col 65}{space 3}0.006{col 73}{space 4} .0733458{col 86}{space 3} .4461829
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Income, Model, uncomfortable, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str6}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.education i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(25, 1330)       =  {res}     2.98
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0360
                                                {txt}Root MSE          =    {res} .28367

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0345646{col 45}{space 2} .0166902{col 56}{space 1}   -2.07{col 65}{space 3}0.039{col 73}{space 4}-.0673066{col 86}{space 3}-.0018226
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0365715{col 45}{space 2} .0291593{col 56}{space 1}   -1.25{col 65}{space 3}0.210{col 73}{space 4}-.0937748{col 86}{space 3} .0206318
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1177871{col 45}{space 2}  .048027{col 56}{space 1}    2.45{col 65}{space 3}0.014{col 73}{space 4}   .02357{col 86}{space 3} .2120041
{txt}{space 25}female {c |}{col 33}{res}{space 2}  .028316{col 45}{space 2} .0158684{col 56}{space 1}    1.78{col 65}{space 3}0.075{col 73}{space 4}-.0028138{col 86}{space 3} .0594458
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0289619{col 45}{space 2} .0633741{col 56}{space 1}    0.46{col 65}{space 3}0.648{col 73}{space 4}-.0953622{col 86}{space 3}  .153286
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0654802{col 45}{space 2} .0407089{col 56}{space 1}    1.61{col 65}{space 3}0.108{col 73}{space 4}-.0143805{col 86}{space 3} .1453409
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0048702{col 45}{space 2} .0294306{col 56}{space 1}    0.17{col 65}{space 3}0.869{col 73}{space 4}-.0528652{col 86}{space 3} .0626056
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0109067{col 45}{space 2} .0265652{col 56}{space 1}    0.41{col 65}{space 3}0.681{col 73}{space 4}-.0412075{col 86}{space 3}  .063021
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}  .008148{col 45}{space 2} .0243824{col 56}{space 1}    0.33{col 65}{space 3}0.738{col 73}{space 4}-.0396842{col 86}{space 3} .0559802
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0391416{col 45}{space 2}  .024995{col 56}{space 1}   -1.57{col 65}{space 3}0.118{col 73}{space 4}-.0881755{col 86}{space 3} .0098924
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0177987{col 45}{space 2} .0380488{col 56}{space 1}   -0.47{col 65}{space 3}0.640{col 73}{space 4}-.0924408{col 86}{space 3} .0568435
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0631101{col 45}{space 2} .0693773{col 56}{space 1}    0.91{col 65}{space 3}0.363{col 73}{space 4}-.0729907{col 86}{space 3} .1992109
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0892269{col 45}{space 2} .0314683{col 56}{space 1}   -2.84{col 65}{space 3}0.005{col 73}{space 4}-.1509599{col 86}{space 3}-.0274939
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0727006{col 45}{space 2} .0300055{col 56}{space 1}   -2.42{col 65}{space 3}0.016{col 73}{space 4}-.1315638{col 86}{space 3}-.0138375
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0949011{col 45}{space 2} .0896831{col 56}{space 1}   -1.06{col 65}{space 3}0.290{col 73}{space 4}-.2708368{col 86}{space 3} .0810347
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0694944{col 45}{space 2} .0891665{col 56}{space 1}   -0.78{col 65}{space 3}0.436{col 73}{space 4}-.2444168{col 86}{space 3} .1054279
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.115004{col 45}{space 2} .0893219{col 56}{space 1}   -1.29{col 65}{space 3}0.198{col 73}{space 4}-.2902312{col 86}{space 3} .0602232
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1096161{col 45}{space 2}  .088635{col 56}{space 1}   -1.24{col 65}{space 3}0.216{col 73}{space 4}-.2834958{col 86}{space 3} .0642636
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1032968{col 45}{space 2} .0892688{col 56}{space 1}   -1.16{col 65}{space 3}0.247{col 73}{space 4}-.2784198{col 86}{space 3} .0718262
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .060967{col 45}{space 2}   .03755{col 56}{space 1}    1.62{col 65}{space 3}0.105{col 73}{space 4}-.0126967{col 86}{space 3} .1346307
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0180663{col 45}{space 2} .0322667{col 56}{space 1}    0.56{col 65}{space 3}0.576{col 73}{space 4}-.0452329{col 86}{space 3} .0813654
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .037454{col 45}{space 2} .0364719{col 56}{space 1}    1.03{col 65}{space 3}0.305{col 73}{space 4}-.0340947{col 86}{space 3} .1090027
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0042394{col 45}{space 2} .0328795{col 56}{space 1}    0.13{col 65}{space 3}0.897{col 73}{space 4}-.0602619{col 86}{space 3} .0687407
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0487448{col 45}{space 2} .0320161{col 56}{space 1}   -1.52{col 65}{space 3}0.128{col 73}{space 4}-.1115525{col 86}{space 3} .0140628
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0435309{col 45}{space 2} .0356015{col 56}{space 1}   -1.22{col 65}{space 3}0.222{col 73}{space 4}-.1133721{col 86}{space 3} .0263104
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1672128{col 45}{space 2} .0925174{col 56}{space 1}    1.81{col 65}{space 3}0.071{col 73}{space 4}-.0142831{col 86}{space 3} .3487088
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Age and age squared, Model, uncomfortable, FE, Without region fixed effects)
{txt}{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income age age_sq i.TAMUNI, r

{txt}Linear regression                               Number of obs     = {res}     1,357
                                                {txt}F(22, 1334)       =  {res}     3.55
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0325
                                                {txt}Root MSE          =    {res} .28378

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0322626{col 45}{space 2} .0165816{col 56}{space 1}   -1.95{col 65}{space 3}0.052{col 73}{space 4}-.0647914{col 86}{space 3} .0002663
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0352912{col 45}{space 2}  .029807{col 56}{space 1}   -1.18{col 65}{space 3}0.237{col 73}{space 4}-.0937648{col 86}{space 3} .0231824
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1135781{col 45}{space 2} .0478575{col 56}{space 1}    2.37{col 65}{space 3}0.018{col 73}{space 4}  .019694{col 86}{space 3} .2074622
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0274832{col 45}{space 2} .0157701{col 56}{space 1}    1.74{col 65}{space 3}0.082{col 73}{space 4}-.0034537{col 86}{space 3} .0584201
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0331502{col 45}{space 2} .0627237{col 56}{space 1}    0.53{col 65}{space 3}0.597{col 73}{space 4}-.0898976{col 86}{space 3} .1561979
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0673569{col 45}{space 2} .0416342{col 56}{space 1}    1.62{col 65}{space 3}0.106{col 73}{space 4}-.0143187{col 86}{space 3} .1490324
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0071364{col 45}{space 2} .0302098{col 56}{space 1}    0.24{col 65}{space 3}0.813{col 73}{space 4}-.0521276{col 86}{space 3} .0664003
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0135615{col 45}{space 2} .0294519{col 56}{space 1}    0.46{col 65}{space 3}0.645{col 73}{space 4}-.0442156{col 86}{space 3} .0713387
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0066919{col 45}{space 2} .0279957{col 56}{space 1}    0.24{col 65}{space 3}0.811{col 73}{space 4}-.0482284{col 86}{space 3} .0616122
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0456178{col 45}{space 2} .0276663{col 56}{space 1}   -1.65{col 65}{space 3}0.099{col 73}{space 4} -.099892{col 86}{space 3} .0086565
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0237488{col 45}{space 2}   .04087{col 56}{space 1}   -0.58{col 65}{space 3}0.561{col 73}{space 4}-.1039252{col 86}{space 3} .0564277
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0603227{col 45}{space 2} .0689062{col 56}{space 1}    0.88{col 65}{space 3}0.381{col 73}{space 4}-.0748535{col 86}{space 3}  .195499
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0927065{col 45}{space 2} .0297194{col 56}{space 1}   -3.12{col 65}{space 3}0.002{col 73}{space 4}-.1510083{col 86}{space 3}-.0344046
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0842078{col 45}{space 2}  .031523{col 56}{space 1}   -2.67{col 65}{space 3}0.008{col 73}{space 4}-.1460479{col 86}{space 3}-.0223677
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0017978{col 45}{space 2} .0031266{col 56}{space 1}   -0.57{col 65}{space 3}0.565{col 73}{space 4}-.0079314{col 86}{space 3} .0043359
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000241{col 45}{space 2} .0000324{col 56}{space 1}    0.75{col 65}{space 3}0.456{col 73}{space 4}-.0000394{col 86}{space 3} .0000877
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0599233{col 45}{space 2} .0378521{col 56}{space 1}    1.58{col 65}{space 3}0.114{col 73}{space 4}-.0143328{col 86}{space 3} .1341794
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0190365{col 45}{space 2} .0331722{col 56}{space 1}    0.57{col 65}{space 3}0.566{col 73}{space 4}-.0460389{col 86}{space 3} .0841118
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0342488{col 45}{space 2} .0369282{col 56}{space 1}    0.93{col 65}{space 3}0.354{col 73}{space 4}-.0381949{col 86}{space 3} .1066925
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0023511{col 45}{space 2} .0329244{col 56}{space 1}    0.07{col 65}{space 3}0.943{col 73}{space 4}-.0622381{col 86}{space 3} .0669403
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0538814{col 45}{space 2} .0323453{col 56}{space 1}   -1.67{col 65}{space 3}0.096{col 73}{space 4}-.1173345{col 86}{space 3} .0095718
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0453626{col 45}{space 2} .0358896{col 56}{space 1}   -1.26{col 65}{space 3}0.206{col 73}{space 4}-.1157688{col 86}{space 3} .0250437
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .0969928{col 45}{space 2} .0719354{col 56}{space 1}    1.35{col 65}{space 3}0.178{col 73}{space 4}-.0441261{col 86}{space 3} .2381117
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Education, Model, uncomfortable, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str9}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income age age_sq i.education, r

{txt}Linear regression                               Number of obs     = {res}     1,356
                                                {txt}F(21, 1334)       =  {res}     4.41
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0247
                                                {txt}Root MSE          =    {res} .28491

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}         uncomfortable{col 24}{c |} Coefficient{col 36}  std. err.{col 48}      t{col 56}   P>|t|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}cabine_use {c |}{col 24}{res}{space 2}-.0189155{col 36}{space 2}  .016494{col 47}{space 1}   -1.15{col 56}{space 3}0.252{col 64}{space 4}-.0512725{col 77}{space 3} .0134415
{txt}{space 14}pp_dummy {c |}{col 24}{res}{space 2}-.0401891{col 36}{space 2} .0300956{col 47}{space 1}   -1.34{col 56}{space 3}0.182{col 64}{space 4} -.099229{col 77}{space 3} .0188508
{txt}{space 3}cabine_use_pp_dummy {c |}{col 24}{res}{space 2} .1257105{col 36}{space 2} .0477886{col 47}{space 1}    2.63{col 56}{space 3}0.009{col 64}{space 4} .0319616{col 77}{space 3} .2194595
{txt}{space 16}female {c |}{col 24}{res}{space 2} .0279576{col 36}{space 2} .0160518{col 47}{space 1}    1.74{col 56}{space 3}0.082{col 64}{space 4} -.003532{col 77}{space 3} .0594471
{txt}{space 22} {c |}
{space 16}income {c |}
Menos o igual a 300 €  {c |}{col 24}{res}{space 2} .0238241{col 36}{space 2} .0637905{col 47}{space 1}    0.37{col 56}{space 3}0.709{col 64}{space 4}-.1013164{col 77}{space 3} .1489647
{txt}{space 7}De 301 a 600 €  {c |}{col 24}{res}{space 2} .0686293{col 36}{space 2} .0417296{col 47}{space 1}    1.64{col 56}{space 3}0.100{col 64}{space 4}-.0132334{col 77}{space 3} .1504921
{txt}{space 7}De 601 a 900 €  {c |}{col 24}{res}{space 2} .0012665{col 36}{space 2}  .030778{col 47}{space 1}    0.04{col 56}{space 3}0.967{col 64}{space 4} -.059112{col 77}{space 3}  .061645
{txt}{space 5}De 901 a 1.200 €  {c |}{col 24}{res}{space 2} .0082246{col 36}{space 2} .0291872{col 47}{space 1}    0.28{col 56}{space 3}0.778{col 64}{space 4}-.0490333{col 77}{space 3} .0654825
{txt}{space 3}De 1.201 a 1.800 €  {c |}{col 24}{res}{space 2}  .005395{col 36}{space 2} .0279205{col 47}{space 1}    0.19{col 56}{space 3}0.847{col 64}{space 4}-.0493777{col 77}{space 3} .0601678
{txt}{space 3}De 1.801 a 2.400 €  {c |}{col 24}{res}{space 2}-.0374543{col 36}{space 2} .0291452{col 47}{space 1}   -1.29{col 56}{space 3}0.199{col 64}{space 4}-.0946297{col 77}{space 3}  .019721
{txt}{space 3}De 2.401 a 3.000 €  {c |}{col 24}{res}{space 2}-.0274802{col 36}{space 2} .0424847{col 47}{space 1}   -0.65{col 56}{space 3}0.518{col 64}{space 4}-.1108244{col 77}{space 3}  .055864
{txt}{space 3}De 3.001 a 4.500 €  {c |}{col 24}{res}{space 2} .0551094{col 36}{space 2} .0710493{col 47}{space 1}    0.78{col 56}{space 3}0.438{col 64}{space 4} -.084271{col 77}{space 3} .1944898
{txt}{space 3}De 4.501 a 6.000 €  {c |}{col 24}{res}{space 2}-.0796096{col 36}{space 2} .0316605{col 47}{space 1}   -2.51{col 56}{space 3}0.012{col 64}{space 4}-.1417193{col 77}{space 3}-.0174999
{txt}{space 7}Más de 6.000 €  {c |}{col 24}{res}{space 2}-.0535342{col 36}{space 2} .0275653{col 47}{space 1}   -1.94{col 56}{space 3}0.052{col 64}{space 4}-.1076102{col 77}{space 3} .0005419
{txt}{space 22} {c |}
{space 19}age {c |}{col 24}{res}{space 2}-.0022354{col 36}{space 2}  .003146{col 47}{space 1}   -0.71{col 56}{space 3}0.477{col 64}{space 4}-.0084071{col 77}{space 3} .0039363
{txt}{space 16}age_sq {c |}{col 24}{res}{space 2} .0000242{col 36}{space 2} .0000333{col 47}{space 1}    0.73{col 56}{space 3}0.467{col 64}{space 4}-.0000411{col 77}{space 3} .0000895
{txt}{space 22} {c |}
{space 13}education {c |}
{space 13}Primaria  {c |}{col 24}{res}{space 2}-.0935315{col 36}{space 2} .0906993{col 47}{space 1}   -1.03{col 56}{space 3}0.303{col 64}{space 4}-.2714603{col 77}{space 3} .0843973
{txt}{space 2}Secundaria 1ª etapa  {c |}{col 24}{res}{space 2}-.0577573{col 36}{space 2} .0915041{col 47}{space 1}   -0.63{col 56}{space 3}0.528{col 64}{space 4}-.2372649{col 77}{space 3} .1217504
{txt}{space 2}Secundaria 2ª etapa  {c |}{col 24}{res}{space 2}-.1056523{col 36}{space 2} .0917057{col 47}{space 1}   -1.15{col 56}{space 3}0.249{col 64}{space 4}-.2855553{col 77}{space 3} .0742508
{txt}{space 17}F.P.  {c |}{col 24}{res}{space 2}-.0983112{col 36}{space 2} .0912604{col 47}{space 1}   -1.08{col 56}{space 3}0.282{col 64}{space 4}-.2773407{col 77}{space 3} .0807184
{txt}{space 11}Superiores  {c |}{col 24}{res}{space 2} -.096386{col 36}{space 2} .0915634{col 47}{space 1}   -1.05{col 56}{space 3}0.293{col 64}{space 4}-.2760099{col 77}{space 3} .0832378
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} .2109795{col 36}{space 2} .1038991{col 47}{space 1}    2.03{col 56}{space 3}0.042{col 64}{space 4}  .007156{col 77}{space 3}  .414803
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. est store pp_fe_controls
{txt}
{com}. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) append addlabel ///
> (Removed, Mun Size, Model, uncomfortable, FE, Without region fixed effects)
{txt}{p 0 7 2}
(variable
{bf:Removed} was {bf:str8}, now {bf:str19} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_data_2.dta{rm}
saved
{p_end}

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured9_1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * A fake model to start the dataset
. regr cabine_use CCAA

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,848
{txt}{hline 13}{c +}{hline 34}   F(1, 1846)      = {res}     4.17
{txt}       Model {c |} {res} 1.02665746         1  1.02665746   {txt}Prob > F        ={res}    0.0414
{txt}    Residual {c |} {res} 455.007433     1,846    .2464829   {txt}R-squared       ={res}    0.0023
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0017
{txt}       Total {c |} {res} 456.034091     1,847  .246905301   {txt}Root MSE        =   {res} .49647

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}CCAA {c |}{col 14}{res}{space 2}-.0046489{col 26}{space 2} .0022779{col 37}{space 1}   -2.04{col 46}{space 3}0.041{col 54}{space 4}-.0091163{col 67}{space 3}-.0001814
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4829034{col 26}{space 2} .0226314{col 37}{space 1}   21.34{col 46}{space 3}0.000{col 54}{space 4} .4385175{col 67}{space 3} .5272892
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regsave CCAA using 01_data/survey_ccaa_jk.dta, ci level(95) replace addlabel ///
> (Removed, fake, Model, fake, Controls, fake)
{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

{com}. 
. * Actual analyses
. forvalues x = 1/19{c -(}
{txt}  2{com}.         regr cabine_use pp_dummy female i.income age age_sq i.education i.TAMUNI i.CCAA if CCAA != `x', r
{txt}  3{com}.         regsave pp_dummy using 01_data/survey_ccaa_jk.dta, ci level(95) append addlabel ///
> (Removed, `x', Model, cabine_use, Controls, With controls)
{txt}  4{com}. 
.         regr cabine_use pp_dummy if CCAA != `x', r
{txt}  5{com}.         regsave pp_dummy using 01_data/survey_ccaa_jk.dta, ci level(95) append addlabel ///
> (Removed, `x', Model, cabine_use, Controls, Without controls)
{txt}  6{com}. {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,125
                                                {txt}F(42, 1082)       =  {res}    19.91
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2825
                                                {txt}Root MSE          =    {res} .43038

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0681994{col 45}{space 2} .0378275{col 56}{space 1}    1.80{col 65}{space 3}0.072{col 73}{space 4}-.0060242{col 86}{space 3} .1424229
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0204183{col 45}{space 2} .0279886{col 56}{space 1}   -0.73{col 65}{space 3}0.466{col 73}{space 4}-.0753363{col 86}{space 3} .0344997
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0260729{col 45}{space 2} .0997699{col 56}{space 1}    0.26{col 65}{space 3}0.794{col 73}{space 4}-.1696914{col 86}{space 3} .2218373
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0057851{col 45}{space 2} .0626921{col 56}{space 1}   -0.09{col 65}{space 3}0.926{col 73}{space 4} -.128797{col 86}{space 3} .1172268
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0370335{col 45}{space 2}  .048063{col 56}{space 1}   -0.77{col 65}{space 3}0.441{col 73}{space 4}-.1313407{col 86}{space 3} .0572738
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0207254{col 45}{space 2} .0451154{col 56}{space 1}   -0.46{col 65}{space 3}0.646{col 73}{space 4}-.1092491{col 86}{space 3} .0677983
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}  -.01268{col 45}{space 2} .0477897{col 56}{space 1}   -0.27{col 65}{space 3}0.791{col 73}{space 4}-.1064509{col 86}{space 3} .0810909
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0009288{col 45}{space 2}  .056522{col 56}{space 1}    0.02{col 65}{space 3}0.987{col 73}{space 4}-.1099764{col 86}{space 3}  .111834
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0183867{col 45}{space 2} .0776132{col 56}{space 1}   -0.24{col 65}{space 3}0.813{col 73}{space 4}-.1706762{col 86}{space 3} .1339027
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1362715{col 45}{space 2} .1233353{col 56}{space 1}    1.10{col 65}{space 3}0.269{col 73}{space 4} -.105732{col 86}{space 3}  .378275
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4146879{col 45}{space 2} .1802459{col 56}{space 1}   -2.30{col 65}{space 3}0.022{col 73}{space 4} -.768359{col 86}{space 3}-.0610167
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .2309938{col 45}{space 2} .1602285{col 56}{space 1}    1.44{col 65}{space 3}0.150{col 73}{space 4}   -.0834{col 86}{space 3} .5453877
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0022859{col 45}{space 2} .0048683{col 56}{space 1}    0.47{col 65}{space 3}0.639{col 73}{space 4}-.0072664{col 86}{space 3} .0118382
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000482{col 45}{space 2} .0000505{col 56}{space 1}   -0.95{col 65}{space 3}0.340{col 73}{space 4}-.0001474{col 86}{space 3} .0000509
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}  .005705{col 45}{space 2} .1186763{col 56}{space 1}    0.05{col 65}{space 3}0.962{col 73}{space 4}-.2271567{col 86}{space 3} .2385667
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0769112{col 45}{space 2} .1200075{col 56}{space 1}   -0.64{col 65}{space 3}0.522{col 73}{space 4} -.312385{col 86}{space 3} .1585627
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1337332{col 45}{space 2} .1212899{col 56}{space 1}   -1.10{col 65}{space 3}0.270{col 73}{space 4}-.3717232{col 86}{space 3} .1042568
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0767356{col 45}{space 2} .1203559{col 56}{space 1}   -0.64{col 65}{space 3}0.524{col 73}{space 4}-.3128931{col 86}{space 3} .1594218
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0755217{col 45}{space 2} .1213447{col 56}{space 1}   -0.62{col 65}{space 3}0.534{col 73}{space 4}-.3136192{col 86}{space 3} .1625759
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0403455{col 45}{space 2} .0614789{col 56}{space 1}    0.66{col 65}{space 3}0.512{col 73}{space 4}-.0802857{col 86}{space 3} .1609768
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1303661{col 45}{space 2} .0601027{col 56}{space 1}   -2.17{col 65}{space 3}0.030{col 73}{space 4}-.2482971{col 86}{space 3}-.0124351
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.2242952{col 45}{space 2} .0679231{col 56}{space 1}   -3.30{col 65}{space 3}0.001{col 73}{space 4}-.3575711{col 86}{space 3}-.0910193
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2218732{col 45}{space 2} .0618516{col 56}{space 1}   -3.59{col 65}{space 3}0.000{col 73}{space 4} -.343236{col 86}{space 3}-.1005105
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3628071{col 45}{space 2}  .075172{col 56}{space 1}   -4.83{col 65}{space 3}0.000{col 73}{space 4}-.5103065{col 86}{space 3}-.2153077
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2437224{col 45}{space 2} .0646848{col 56}{space 1}   -3.77{col 65}{space 3}0.000{col 73}{space 4}-.3706443{col 86}{space 3}-.1168006
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} -.184351{col 45}{space 2} .0931543{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4}-.3671346{col 86}{space 3}-.0015675
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1668563{col 45}{space 2} .0901235{col 56}{space 1}   -1.85{col 65}{space 3}0.064{col 73}{space 4}-.3436929{col 86}{space 3} .0099804
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}  .401202{col 45}{space 2} .0790157{col 56}{space 1}    5.08{col 65}{space 3}0.000{col 73}{space 4} .2461606{col 86}{space 3} .5562434
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0339674{col 45}{space 2} .0873198{col 56}{space 1}   -0.39{col 65}{space 3}0.697{col 73}{space 4}-.2053028{col 86}{space 3}  .137368
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0483412{col 45}{space 2} .0918212{col 56}{space 1}    0.53{col 65}{space 3}0.599{col 73}{space 4}-.1318266{col 86}{space 3} .2285089
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0803127{col 45}{space 2} .0902978{col 56}{space 1}    0.89{col 65}{space 3}0.374{col 73}{space 4} -.096866{col 86}{space 3} .2574914
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4096065{col 45}{space 2} .0749891{col 56}{space 1}   -5.46{col 65}{space 3}0.000{col 73}{space 4}-.5567471{col 86}{space 3} -.262466
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0515426{col 45}{space 2} .0749791{col 56}{space 1}   -0.69{col 65}{space 3}0.492{col 73}{space 4}-.1986635{col 86}{space 3} .0955783
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}  .182382{col 45}{space 2} .0814953{col 56}{space 1}    2.24{col 65}{space 3}0.025{col 73}{space 4} .0224753{col 86}{space 3} .3422888
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} .0002142{col 45}{space 2} .0915765{col 56}{space 1}    0.00{col 65}{space 3}0.998{col 73}{space 4}-.1794736{col 86}{space 3} .1799019
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3565488{col 45}{space 2} .0754137{col 56}{space 1}   -4.73{col 65}{space 3}0.000{col 73}{space 4}-.5045224{col 86}{space 3}-.2085752
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1629894{col 45}{space 2} .0842067{col 56}{space 1}    1.94{col 65}{space 3}0.053{col 73}{space 4}-.0022375{col 86}{space 3} .3282162
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1820279{col 45}{space 2} .1065662{col 56}{space 1}   -1.71{col 65}{space 3}0.088{col 73}{space 4}-.3911278{col 86}{space 3} .0270719
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0771664{col 45}{space 2} .1080923{col 56}{space 1}   -0.71{col 65}{space 3}0.475{col 73}{space 4}-.2892606{col 86}{space 3} .1349279
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0360282{col 45}{space 2} .1208085{col 56}{space 1}   -0.30{col 65}{space 3}0.766{col 73}{space 4}-.2730737{col 86}{space 3} .2010173
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .3403669{col 45}{space 2} .1096625{col 56}{space 1}    3.10{col 65}{space 3}0.002{col 73}{space 4} .1251918{col 86}{space 3} .5555421
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2103251{col 45}{space 2} .1341861{col 56}{space 1}    1.57{col 65}{space 3}0.117{col 73}{space 4}-.0529693{col 86}{space 3} .4736195
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .7934358{col 45}{space 2} .1686178{col 56}{space 1}    4.71{col 65}{space 3}0.000{col 73}{space 4} .4625809{col 86}{space 3} 1.124291
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(note: variable
{bf:Removed} was str4 in the using data, but will be
byte now)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,554
                                                {txt}F(1, 1552)        =  {res}     7.64
                                                {txt}Prob > F          = {res}    0.0058
                                                {txt}R-squared         = {res}    0.0050
                                                {txt}Root MSE          =    {res} .49308

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1030201{col 26}{space 2} .0372595{col 37}{space 1}    2.76{col 46}{space 3}0.006{col 54}{space 4} .0299359{col 67}{space 3} .1761044
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4090572{col 26}{space 2} .0134048{col 37}{space 1}   30.52{col 46}{space 3}0.000{col 54}{space 4} .3827637{col 67}{space 3} .4353506
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,298
                                                {txt}F(42, 1255)       =  {res}    19.79
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2481
                                                {txt}Root MSE          =    {res} .44042

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0899208{col 45}{space 2} .0352731{col 56}{space 1}    2.55{col 65}{space 3}0.011{col 73}{space 4} .0207199{col 86}{space 3} .1591216
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0185586{col 45}{space 2} .0265585{col 56}{space 1}   -0.70{col 65}{space 3}0.485{col 73}{space 4}-.0706626{col 86}{space 3} .0335454
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0008547{col 45}{space 2} .0956785{col 56}{space 1}   -0.01{col 65}{space 3}0.993{col 73}{space 4}-.1885621{col 86}{space 3} .1868527
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0036721{col 45}{space 2} .0568865{col 56}{space 1}   -0.06{col 65}{space 3}0.949{col 73}{space 4}-.1152752{col 86}{space 3} .1079311
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0321461{col 45}{space 2} .0454127{col 56}{space 1}   -0.71{col 65}{space 3}0.479{col 73}{space 4}-.1212392{col 86}{space 3}  .056947
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0483904{col 45}{space 2} .0428665{col 56}{space 1}   -1.13{col 65}{space 3}0.259{col 73}{space 4}-.1324883{col 86}{space 3} .0357074
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0332474{col 45}{space 2} .0451754{col 56}{space 1}   -0.74{col 65}{space 3}0.462{col 73}{space 4} -.121875{col 86}{space 3} .0553801
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0018454{col 45}{space 2} .0545491{col 56}{space 1}    0.03{col 65}{space 3}0.973{col 73}{space 4}-.1051721{col 86}{space 3} .1088629
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0401503{col 45}{space 2} .0731721{col 56}{space 1}   -0.55{col 65}{space 3}0.583{col 73}{space 4}-.1837035{col 86}{space 3} .1034028
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1537266{col 45}{space 2} .1160326{col 56}{space 1}    1.32{col 65}{space 3}0.185{col 73}{space 4}-.0739127{col 86}{space 3} .3813659
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4363391{col 45}{space 2} .1792098{col 56}{space 1}   -2.43{col 65}{space 3}0.015{col 73}{space 4} -.787923{col 86}{space 3}-.0847553
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0222427{col 45}{space 2} .2081411{col 56}{space 1}    0.11{col 65}{space 3}0.915{col 73}{space 4}-.3861001{col 86}{space 3} .4305855
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0002796{col 45}{space 2} .0046383{col 56}{space 1}   -0.06{col 65}{space 3}0.952{col 73}{space 4}-.0093794{col 86}{space 3} .0088201
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000204{col 45}{space 2} .0000484{col 56}{space 1}   -0.42{col 65}{space 3}0.673{col 73}{space 4}-.0001155{col 86}{space 3} .0000746
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0683189{col 45}{space 2} .1057032{col 56}{space 1}   -0.65{col 65}{space 3}0.518{col 73}{space 4}-.2756933{col 86}{space 3} .1390556
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1400757{col 45}{space 2} .1064347{col 56}{space 1}   -1.32{col 65}{space 3}0.188{col 73}{space 4}-.3488852{col 86}{space 3} .0687338
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.174696{col 45}{space 2} .1082385{col 56}{space 1}   -1.61{col 65}{space 3}0.107{col 73}{space 4}-.3870444{col 86}{space 3} .0376524
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0930827{col 45}{space 2} .1074272{col 56}{space 1}   -0.87{col 65}{space 3}0.386{col 73}{space 4}-.3038394{col 86}{space 3} .1176739
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}  -.10549{col 45}{space 2} .1091355{col 56}{space 1}   -0.97{col 65}{space 3}0.334{col 73}{space 4}-.3195981{col 86}{space 3} .1086182
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0100112{col 45}{space 2} .0636493{col 56}{space 1}    0.16{col 65}{space 3}0.875{col 73}{space 4}-.1148595{col 86}{space 3} .1348818
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1153435{col 45}{space 2} .0620861{col 56}{space 1}   -1.86{col 65}{space 3}0.063{col 73}{space 4}-.2371475{col 86}{space 3} .0064605
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1750179{col 45}{space 2} .0682134{col 56}{space 1}   -2.57{col 65}{space 3}0.010{col 73}{space 4}-.3088427{col 86}{space 3}-.0411931
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2090946{col 45}{space 2} .0631818{col 56}{space 1}   -3.31{col 65}{space 3}0.001{col 73}{space 4}-.3330482{col 86}{space 3}-.0851411
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3368565{col 45}{space 2} .0769021{col 56}{space 1}   -4.38{col 65}{space 3}0.000{col 73}{space 4}-.4877274{col 86}{space 3}-.1859856
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2315317{col 45}{space 2} .0668329{col 56}{space 1}   -3.46{col 65}{space 3}0.001{col 73}{space 4}-.3626482{col 86}{space 3}-.1004153
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2225233{col 45}{space 2} .0725262{col 56}{space 1}   -3.07{col 65}{space 3}0.002{col 73}{space 4}-.3648094{col 86}{space 3}-.0802373
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1994603{col 45}{space 2} .0774532{col 56}{space 1}   -2.58{col 65}{space 3}0.010{col 73}{space 4}-.3514124{col 86}{space 3}-.0475082
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3688893{col 45}{space 2} .0541775{col 56}{space 1}    6.81{col 65}{space 3}0.000{col 73}{space 4} .2626009{col 86}{space 3} .4751778
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0538827{col 45}{space 2} .0692277{col 56}{space 1}   -0.78{col 65}{space 3}0.437{col 73}{space 4}-.1896975{col 86}{space 3}  .081932
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0102006{col 45}{space 2} .0713097{col 56}{space 1}    0.14{col 65}{space 3}0.886{col 73}{space 4}-.1296987{col 86}{space 3} .1500999
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0539193{col 45}{space 2} .0717507{col 56}{space 1}    0.75{col 65}{space 3}0.453{col 73}{space 4}-.0868452{col 86}{space 3} .1946837
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4363292{col 45}{space 2}  .048545{col 56}{space 1}   -8.99{col 65}{space 3}0.000{col 73}{space 4}-.5315676{col 86}{space 3}-.3410908
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0822039{col 45}{space 2} .0545818{col 56}{space 1}   -1.51{col 65}{space 3}0.132{col 73}{space 4}-.1892855{col 86}{space 3} .0248777
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1590074{col 45}{space 2} .0617586{col 56}{space 1}    2.57{col 65}{space 3}0.010{col 73}{space 4} .0378458{col 86}{space 3}  .280169
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0267311{col 45}{space 2} .0722272{col 56}{space 1}   -0.37{col 65}{space 3}0.711{col 73}{space 4}-.1684305{col 86}{space 3} .1149683
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3910271{col 45}{space 2} .0475256{col 56}{space 1}   -8.23{col 65}{space 3}0.000{col 73}{space 4}-.4842655{col 86}{space 3}-.2977886
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}  .125054{col 45}{space 2} .0662188{col 56}{space 1}    1.89{col 65}{space 3}0.059{col 73}{space 4}-.0048578{col 86}{space 3} .2549658
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2009134{col 45}{space 2} .0912364{col 56}{space 1}   -2.20{col 65}{space 3}0.028{col 73}{space 4}-.3799062{col 86}{space 3}-.0219207
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.115774{col 45}{space 2} .0893771{col 56}{space 1}   -1.30{col 65}{space 3}0.195{col 73}{space 4} -.291119{col 86}{space 3} .0595709
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} -.065835{col 45}{space 2} .1063899{col 56}{space 1}   -0.62{col 65}{space 3}0.536{col 73}{space 4}-.2745567{col 86}{space 3} .1428866
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2706457{col 45}{space 2} .0874137{col 56}{space 1}    3.10{col 65}{space 3}0.002{col 73}{space 4} .0991527{col 86}{space 3} .4421388
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1421763{col 45}{space 2} .1153655{col 56}{space 1}    1.23{col 65}{space 3}0.218{col 73}{space 4}-.0841542{col 86}{space 3} .3685067
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9114576{col 45}{space 2} .1481836{col 56}{space 1}    6.15{col 65}{space 3}0.000{col 73}{space 4} .6207427{col 86}{space 3} 1.202173
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,772
                                                {txt}F(1, 1770)        =  {res}    10.29
                                                {txt}Prob > F          = {res}    0.0014
                                                {txt}R-squared         = {res}    0.0058
                                                {txt}Root MSE          =    {res}  .4955

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1087406{col 26}{space 2} .0339008{col 37}{space 1}    3.21{col 46}{space 3}0.001{col 54}{space 4} .0422508{col 67}{space 3} .1752304
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4269737{col 26}{space 2} .0126944{col 37}{space 1}   33.63{col 46}{space 3}0.000{col 54}{space 4} .4020761{col 67}{space 3} .4518712
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,306
                                                {txt}F(42, 1263)       =  {res}    20.02
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2517
                                                {txt}Root MSE          =    {res} .43958

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2}  .089515{col 45}{space 2} .0349674{col 56}{space 1}    2.56{col 65}{space 3}0.011{col 73}{space 4} .0209145{col 86}{space 3} .1581155
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0130638{col 45}{space 2} .0263359{col 56}{space 1}   -0.50{col 65}{space 3}0.620{col 73}{space 4}-.0647307{col 86}{space 3} .0386031
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}  .013978{col 45}{space 2} .0928871{col 56}{space 1}    0.15{col 65}{space 3}0.880{col 73}{space 4} -.168252{col 86}{space 3}  .196208
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0037246{col 45}{space 2} .0570313{col 56}{space 1}   -0.07{col 65}{space 3}0.948{col 73}{space 4} -.115611{col 86}{space 3} .1081619
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0423668{col 45}{space 2} .0455107{col 56}{space 1}   -0.93{col 65}{space 3}0.352{col 73}{space 4}-.1316517{col 86}{space 3} .0469181
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0447899{col 45}{space 2} .0429647{col 56}{space 1}   -1.04{col 65}{space 3}0.297{col 73}{space 4}-.1290799{col 86}{space 3} .0395001
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} -.014749{col 45}{space 2} .0457609{col 56}{space 1}   -0.32{col 65}{space 3}0.747{col 73}{space 4}-.1045248{col 86}{space 3} .0750268
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0101003{col 45}{space 2} .0541808{col 56}{space 1}    0.19{col 65}{space 3}0.852{col 73}{space 4}-.0961939{col 86}{space 3} .1163945
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0176968{col 45}{space 2} .0747446{col 56}{space 1}   -0.24{col 65}{space 3}0.813{col 73}{space 4} -.164334{col 86}{space 3} .1289404
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1533733{col 45}{space 2} .1097412{col 56}{space 1}    1.40{col 65}{space 3}0.162{col 73}{space 4}-.0619218{col 86}{space 3} .3686685
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4164334{col 45}{space 2} .1757302{col 56}{space 1}   -2.37{col 65}{space 3}0.018{col 73}{space 4}-.7611887{col 86}{space 3}-.0716781
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0171034{col 45}{space 2} .2082378{col 56}{space 1}    0.08{col 65}{space 3}0.935{col 73}{space 4}-.3914267{col 86}{space 3} .4256335
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0006797{col 45}{space 2}  .004595{col 56}{space 1}   -0.15{col 65}{space 3}0.882{col 73}{space 4}-.0096943{col 86}{space 3} .0083349
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000113{col 45}{space 2} .0000478{col 56}{space 1}   -0.24{col 65}{space 3}0.813{col 73}{space 4}-.0001051{col 86}{space 3} .0000825
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0375205{col 45}{space 2} .1099308{col 56}{space 1}   -0.34{col 65}{space 3}0.733{col 73}{space 4}-.2531875{col 86}{space 3} .1781465
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1207989{col 45}{space 2}  .111067{col 56}{space 1}   -1.09{col 65}{space 3}0.277{col 73}{space 4}-.3386949{col 86}{space 3} .0970972
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1520536{col 45}{space 2} .1127701{col 56}{space 1}   -1.35{col 65}{space 3}0.178{col 73}{space 4} -.373291{col 86}{space 3} .0691838
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0726603{col 45}{space 2} .1118635{col 56}{space 1}   -0.65{col 65}{space 3}0.516{col 73}{space 4} -.292119{col 86}{space 3} .1467985
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0933711{col 45}{space 2}  .113341{col 56}{space 1}   -0.82{col 65}{space 3}0.410{col 73}{space 4}-.3157285{col 86}{space 3} .1289863
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0007185{col 45}{space 2} .0597275{col 56}{space 1}    0.01{col 65}{space 3}0.990{col 73}{space 4}-.1164575{col 86}{space 3} .1178946
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1214222{col 45}{space 2} .0581373{col 56}{space 1}   -2.09{col 65}{space 3}0.037{col 73}{space 4}-.2354785{col 86}{space 3}-.0073659
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1522136{col 45}{space 2} .0650969{col 56}{space 1}   -2.34{col 65}{space 3}0.020{col 73}{space 4}-.2799237{col 86}{space 3}-.0245036
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}   -.2299{col 45}{space 2} .0601438{col 56}{space 1}   -3.82{col 65}{space 3}0.000{col 73}{space 4}-.3478928{col 86}{space 3}-.1119073
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3805047{col 45}{space 2} .0680117{col 56}{space 1}   -5.59{col 65}{space 3}0.000{col 73}{space 4} -.513933{col 86}{space 3}-.2470763
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2401974{col 45}{space 2} .0637643{col 56}{space 1}   -3.77{col 65}{space 3}0.000{col 73}{space 4} -.365293{col 86}{space 3}-.1151018
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0252167{col 45}{space 2} .0687566{col 56}{space 1}   -0.37{col 65}{space 3}0.714{col 73}{space 4}-.1601064{col 86}{space 3}  .109673
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1878195{col 45}{space 2}  .077884{col 56}{space 1}   -2.41{col 65}{space 3}0.016{col 73}{space 4}-.3406159{col 86}{space 3}-.0350232
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3682351{col 45}{space 2} .0539317{col 56}{space 1}    6.83{col 65}{space 3}0.000{col 73}{space 4} .2624296{col 86}{space 3} .4740407
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0631666{col 45}{space 2} .0681138{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.1967952{col 86}{space 3} .0704621
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0016229{col 45}{space 2} .0709431{col 56}{space 1}   -0.02{col 65}{space 3}0.982{col 73}{space 4}-.1408021{col 86}{space 3} .1375564
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}  .043362{col 45}{space 2} .0713513{col 56}{space 1}    0.61{col 65}{space 3}0.543{col 73}{space 4} -.096618{col 86}{space 3} .1833421
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4441287{col 45}{space 2} .0483219{col 56}{space 1}   -9.19{col 65}{space 3}0.000{col 73}{space 4}-.5389288{col 86}{space 3}-.3493286
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0856252{col 45}{space 2} .0545202{col 56}{space 1}   -1.57{col 65}{space 3}0.117{col 73}{space 4}-.1925852{col 86}{space 3} .0213348
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1518449{col 45}{space 2}  .061565{col 56}{space 1}    2.47{col 65}{space 3}0.014{col 73}{space 4} .0310641{col 86}{space 3} .2726258
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0337396{col 45}{space 2} .0726243{col 56}{space 1}   -0.46{col 65}{space 3}0.642{col 73}{space 4}-.1762171{col 86}{space 3} .1087379
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4001278{col 45}{space 2} .0473273{col 56}{space 1}   -8.45{col 65}{space 3}0.000{col 73}{space 4}-.4929766{col 86}{space 3} -.307279
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1321196{col 45}{space 2} .0661756{col 56}{space 1}    2.00{col 65}{space 3}0.046{col 73}{space 4} .0022933{col 86}{space 3} .2619459
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2} -.205092{col 45}{space 2} .0904858{col 56}{space 1}   -2.27{col 65}{space 3}0.024{col 73}{space 4}-.3826109{col 86}{space 3}-.0275731
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1174883{col 45}{space 2} .0884608{col 56}{space 1}   -1.33{col 65}{space 3}0.184{col 73}{space 4}-.2910345{col 86}{space 3} .0560579
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0647216{col 45}{space 2} .1052851{col 56}{space 1}   -0.61{col 65}{space 3}0.539{col 73}{space 4}-.2712746{col 86}{space 3} .1418314
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2316901{col 45}{space 2} .0882533{col 56}{space 1}    2.63{col 65}{space 3}0.009{col 73}{space 4} .0585509{col 86}{space 3} .4048292
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1106579{col 45}{space 2} .1161426{col 56}{space 1}    0.95{col 65}{space 3}0.341{col 73}{space 4}-.1171959{col 86}{space 3} .3385116
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .8955053{col 45}{space 2} .1495522{col 56}{space 1}    5.99{col 65}{space 3}0.000{col 73}{space 4} .6021072{col 86}{space 3} 1.188903
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,785
                                                {txt}F(1, 1783)        =  {res}    10.57
                                                {txt}Prob > F          = {res}    0.0012
                                                {txt}R-squared         = {res}    0.0059
                                                {txt}Root MSE          =    {res} .49599

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1102812{col 26}{space 2} .0339154{col 37}{space 1}    3.25{col 46}{space 3}0.001{col 54}{space 4} .0437631{col 67}{space 3} .1767992
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4315515{col 26}{space 2}  .012653{col 37}{space 1}   34.11{col 46}{space 3}0.000{col 54}{space 4} .4067353{col 67}{space 3} .4563677
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,307
                                                {txt}F(42, 1264)       =  {res}    20.66
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2562
                                                {txt}Root MSE          =    {res} .43828

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1102904{col 45}{space 2} .0352758{col 56}{space 1}    3.13{col 65}{space 3}0.002{col 73}{space 4} .0410848{col 86}{space 3}  .179496
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0184939{col 45}{space 2} .0265277{col 56}{space 1}   -0.70{col 65}{space 3}0.486{col 73}{space 4}-.0705371{col 86}{space 3} .0335493
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}   .00028{col 45}{space 2} .0929612{col 56}{space 1}    0.00{col 65}{space 3}0.998{col 73}{space 4}-.1820952{col 86}{space 3} .1826553
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0028698{col 45}{space 2} .0566697{col 56}{space 1}   -0.05{col 65}{space 3}0.960{col 73}{space 4}-.1140469{col 86}{space 3} .1083073
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}  -.03784{col 45}{space 2} .0451536{col 56}{space 1}   -0.84{col 65}{space 3}0.402{col 73}{space 4}-.1264242{col 86}{space 3} .0507442
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0427397{col 45}{space 2} .0428236{col 56}{space 1}   -1.00{col 65}{space 3}0.318{col 73}{space 4}-.1267528{col 86}{space 3} .0412734
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0239598{col 45}{space 2} .0453884{col 56}{space 1}   -0.53{col 65}{space 3}0.598{col 73}{space 4}-.1130046{col 86}{space 3}  .065085
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0168765{col 45}{space 2} .0538385{col 56}{space 1}   -0.31{col 65}{space 3}0.754{col 73}{space 4}-.1224992{col 86}{space 3} .0887462
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0663176{col 45}{space 2} .0730996{col 56}{space 1}   -0.91{col 65}{space 3}0.364{col 73}{space 4}-.2097274{col 86}{space 3} .0770923
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1636543{col 45}{space 2} .1123539{col 56}{space 1}    1.46{col 65}{space 3}0.145{col 73}{space 4}-.0567663{col 86}{space 3}  .384075
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4359368{col 45}{space 2} .1755896{col 56}{space 1}   -2.48{col 65}{space 3}0.013{col 73}{space 4} -.780416{col 86}{space 3}-.0914576
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0214451{col 45}{space 2} .2151504{col 56}{space 1}    0.10{col 65}{space 3}0.921{col 73}{space 4}-.4006462{col 86}{space 3} .4435363
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0005049{col 45}{space 2} .0045246{col 56}{space 1}    0.11{col 65}{space 3}0.911{col 73}{space 4}-.0083717{col 86}{space 3} .0093815
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000265{col 45}{space 2} .0000469{col 56}{space 1}   -0.56{col 65}{space 3}0.572{col 73}{space 4}-.0001185{col 86}{space 3} .0000655
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0761921{col 45}{space 2} .1076381{col 56}{space 1}   -0.71{col 65}{space 3}0.479{col 73}{space 4} -.287361{col 86}{space 3} .1349768
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1583891{col 45}{space 2} .1084581{col 56}{space 1}   -1.46{col 65}{space 3}0.144{col 73}{space 4}-.3711667{col 86}{space 3} .0543886
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1789279{col 45}{space 2} .1102221{col 56}{space 1}   -1.62{col 65}{space 3}0.105{col 73}{space 4}-.3951664{col 86}{space 3} .0373106
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0999774{col 45}{space 2} .1093288{col 56}{space 1}   -0.91{col 65}{space 3}0.361{col 73}{space 4}-.3144632{col 86}{space 3} .1145085
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1182031{col 45}{space 2} .1107963{col 56}{space 1}   -1.07{col 65}{space 3}0.286{col 73}{space 4} -.335568{col 86}{space 3} .0991618
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0112915{col 45}{space 2} .0600468{col 56}{space 1}    0.19{col 65}{space 3}0.851{col 73}{space 4}-.1065108{col 86}{space 3} .1290939
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1014175{col 45}{space 2} .0586793{col 56}{space 1}   -1.73{col 65}{space 3}0.084{col 73}{space 4}-.2165371{col 86}{space 3} .0137021
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1670208{col 45}{space 2} .0647326{col 56}{space 1}   -2.58{col 65}{space 3}0.010{col 73}{space 4} -.294016{col 86}{space 3}-.0400256
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2078024{col 45}{space 2} .0601984{col 56}{space 1}   -3.45{col 65}{space 3}0.001{col 73}{space 4}-.3259022{col 86}{space 3}-.0897027
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4162216{col 45}{space 2} .0699553{col 56}{space 1}   -5.95{col 65}{space 3}0.000{col 73}{space 4} -.553463{col 86}{space 3}-.2789802
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2250115{col 45}{space 2} .0640548{col 56}{space 1}   -3.51{col 65}{space 3}0.000{col 73}{space 4}-.3506769{col 86}{space 3} -.099346
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0048274{col 45}{space 2} .0686869{col 56}{space 1}   -0.07{col 65}{space 3}0.944{col 73}{space 4}-.1395802{col 86}{space 3} .1299255
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2338498{col 45}{space 2}  .072727{col 56}{space 1}   -3.22{col 65}{space 3}0.001{col 73}{space 4}-.3765287{col 86}{space 3}-.0911709
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3564332{col 45}{space 2} .0542797{col 56}{space 1}    6.57{col 65}{space 3}0.000{col 73}{space 4}  .249945{col 86}{space 3} .4629215
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0689073{col 45}{space 2} .0687105{col 56}{space 1}   -1.00{col 65}{space 3}0.316{col 73}{space 4}-.2037065{col 86}{space 3} .0658918
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0059104{col 45}{space 2} .0710269{col 56}{space 1}   -0.08{col 65}{space 3}0.934{col 73}{space 4} -.145254{col 86}{space 3} .1334332
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0399037{col 45}{space 2} .0710429{col 56}{space 1}    0.56{col 65}{space 3}0.574{col 73}{space 4}-.0994713{col 86}{space 3} .1792787
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4476616{col 45}{space 2} .0483511{col 56}{space 1}   -9.26{col 65}{space 3}0.000{col 73}{space 4}-.5425188{col 86}{space 3}-.3528044
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0809573{col 45}{space 2} .0544887{col 56}{space 1}   -1.49{col 65}{space 3}0.138{col 73}{space 4}-.1878556{col 86}{space 3}  .025941
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1453583{col 45}{space 2} .0611159{col 56}{space 1}    2.38{col 65}{space 3}0.018{col 73}{space 4} .0254586{col 86}{space 3} .2652581
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0429326{col 45}{space 2} .0724308{col 56}{space 1}   -0.59{col 65}{space 3}0.553{col 73}{space 4}-.1850304{col 86}{space 3} .0991652
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4062732{col 45}{space 2} .0473084{col 56}{space 1}   -8.59{col 65}{space 3}0.000{col 73}{space 4}-.4990849{col 86}{space 3}-.3134615
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1367935{col 45}{space 2} .0666995{col 56}{space 1}    2.05{col 65}{space 3}0.040{col 73}{space 4} .0059396{col 86}{space 3} .2676473
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2115199{col 45}{space 2} .0913389{col 56}{space 1}   -2.32{col 65}{space 3}0.021{col 73}{space 4}-.3907124{col 86}{space 3}-.0323273
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.124797{col 45}{space 2} .0885786{col 56}{space 1}   -1.41{col 65}{space 3}0.159{col 73}{space 4}-.2985743{col 86}{space 3} .0489802
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0811231{col 45}{space 2} .1059915{col 56}{space 1}   -0.77{col 65}{space 3}0.444{col 73}{space 4}-.2890618{col 86}{space 3} .1268156
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2516435{col 45}{space 2} .0872801{col 56}{space 1}    2.88{col 65}{space 3}0.004{col 73}{space 4} .0804137{col 86}{space 3} .4228733
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .124319{col 45}{space 2} .1154696{col 56}{space 1}    1.08{col 65}{space 3}0.282{col 73}{space 4}-.1022142{col 86}{space 3} .3508521
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9058576{col 45}{space 2} .1481662{col 56}{space 1}    6.11{col 65}{space 3}0.000{col 73}{space 4} .6151789{col 86}{space 3} 1.196536
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,768
                                                {txt}F(1, 1766)        =  {res}    13.15
                                                {txt}Prob > F          = {res}    0.0003
                                                {txt}R-squared         = {res}    0.0075
                                                {txt}Root MSE          =    {res} .49528

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1245551{col 26}{space 2} .0343465{col 37}{space 1}    3.63{col 46}{space 3}0.000{col 54}{space 4}  .057191{col 67}{space 3} .1919191
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4268852{col 26}{space 2} .0126732{col 37}{space 1}   33.68{col 46}{space 3}0.000{col 54}{space 4} .4020291{col 67}{space 3} .4517414
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,316
                                                {txt}F(42, 1273)       =  {res}    15.98
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2316
                                                {txt}Root MSE          =    {res} .44445

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2}  .096127{col 45}{space 2} .0351931{col 56}{space 1}    2.73{col 65}{space 3}0.006{col 73}{space 4} .0270842{col 86}{space 3} .1651699
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0188216{col 45}{space 2} .0265284{col 56}{space 1}   -0.71{col 65}{space 3}0.478{col 73}{space 4}-.0708657{col 86}{space 3} .0332226
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0088929{col 45}{space 2} .0955223{col 56}{space 1}   -0.09{col 65}{space 3}0.926{col 73}{space 4}-.1962913{col 86}{space 3} .1785055
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .007711{col 45}{space 2} .0575674{col 56}{space 1}    0.13{col 65}{space 3}0.893{col 73}{space 4}-.1052264{col 86}{space 3} .1206485
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0369728{col 45}{space 2}   .04593{col 56}{space 1}   -0.80{col 65}{space 3}0.421{col 73}{space 4}-.1270796{col 86}{space 3} .0531341
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0473069{col 45}{space 2} .0432038{col 56}{space 1}   -1.09{col 65}{space 3}0.274{col 73}{space 4}-.1320653{col 86}{space 3} .0374516
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0222606{col 45}{space 2} .0452461{col 56}{space 1}   -0.49{col 65}{space 3}0.623{col 73}{space 4}-.1110257{col 86}{space 3} .0665044
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0041691{col 45}{space 2} .0546883{col 56}{space 1}    0.08{col 65}{space 3}0.939{col 73}{space 4}-.1031201{col 86}{space 3} .1114582
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0325692{col 45}{space 2} .0733758{col 56}{space 1}   -0.44{col 65}{space 3}0.657{col 73}{space 4}  -.17652{col 86}{space 3} .1113815
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}  .150809{col 45}{space 2} .1098663{col 56}{space 1}    1.37{col 65}{space 3}0.170{col 73}{space 4}-.0647299{col 86}{space 3}  .366348
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.423581{col 45}{space 2} .1820014{col 56}{space 1}   -2.33{col 65}{space 3}0.020{col 73}{space 4}-.7806367{col 86}{space 3}-.0665253
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0231976{col 45}{space 2} .2101223{col 56}{space 1}    0.11{col 65}{space 3}0.912{col 73}{space 4}-.3890265{col 86}{space 3} .4354217
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0003752{col 45}{space 2} .0045767{col 56}{space 1}   -0.08{col 65}{space 3}0.935{col 73}{space 4}-.0093538{col 86}{space 3} .0086035
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000185{col 45}{space 2} .0000476{col 56}{space 1}   -0.39{col 65}{space 3}0.698{col 73}{space 4}-.0001118{col 86}{space 3} .0000748
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0615677{col 45}{space 2} .1055697{col 56}{space 1}   -0.58{col 65}{space 3}0.560{col 73}{space 4}-.2686774{col 86}{space 3} .1455421
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1406011{col 45}{space 2}  .106479{col 56}{space 1}   -1.32{col 65}{space 3}0.187{col 73}{space 4}-.3494947{col 86}{space 3} .0682925
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1649731{col 45}{space 2} .1080988{col 56}{space 1}   -1.53{col 65}{space 3}0.127{col 73}{space 4}-.3770445{col 86}{space 3} .0470983
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0820767{col 45}{space 2} .1072537{col 56}{space 1}   -0.77{col 65}{space 3}0.444{col 73}{space 4}-.2924901{col 86}{space 3} .1283367
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1058093{col 45}{space 2} .1087964{col 56}{space 1}   -0.97{col 65}{space 3}0.331{col 73}{space 4}-.3192493{col 86}{space 3} .1076306
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0042744{col 45}{space 2} .0598599{col 56}{space 1}    0.07{col 65}{space 3}0.943{col 73}{space 4}-.1131604{col 86}{space 3} .1217092
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1312383{col 45}{space 2}  .058479{col 56}{space 1}   -2.24{col 65}{space 3}0.025{col 73}{space 4}-.2459642{col 86}{space 3}-.0165124
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1812328{col 45}{space 2} .0650499{col 56}{space 1}   -2.79{col 65}{space 3}0.005{col 73}{space 4}-.3088497{col 86}{space 3} -.053616
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2189945{col 45}{space 2} .0603639{col 56}{space 1}   -3.63{col 65}{space 3}0.000{col 73}{space 4}-.3374181{col 86}{space 3}-.1005708
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.385457{col 45}{space 2} .0680075{col 56}{space 1}   -5.67{col 65}{space 3}0.000{col 73}{space 4} -.518876{col 86}{space 3}-.2520379
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2414545{col 45}{space 2} .0638761{col 56}{space 1}   -3.78{col 65}{space 3}0.000{col 73}{space 4}-.3667686{col 86}{space 3}-.1161404
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0224431{col 45}{space 2} .0689707{col 56}{space 1}   -0.33{col 65}{space 3}0.745{col 73}{space 4}-.1577518{col 86}{space 3} .1128656
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2293799{col 45}{space 2} .0725295{col 56}{space 1}   -3.16{col 65}{space 3}0.002{col 73}{space 4}-.3716703{col 86}{space 3}-.0870895
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1846581{col 45}{space 2} .0779232{col 56}{space 1}   -2.37{col 65}{space 3}0.018{col 73}{space 4}  -.33753{col 86}{space 3}-.0317862
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0650453{col 45}{space 2} .0686481{col 56}{space 1}   -0.95{col 65}{space 3}0.344{col 73}{space 4}-.1997211{col 86}{space 3} .0696305
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}  .002541{col 45}{space 2} .0710729{col 56}{space 1}    0.04{col 65}{space 3}0.971{col 73}{space 4}-.1368919{col 86}{space 3}  .141974
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0421256{col 45}{space 2} .0712725{col 56}{space 1}    0.59{col 65}{space 3}0.555{col 73}{space 4}-.0976989{col 86}{space 3}   .18195
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4450022{col 45}{space 2} .0482417{col 56}{space 1}   -9.22{col 65}{space 3}0.000{col 73}{space 4}-.5396443{col 86}{space 3}-.3503602
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} -.082414{col 45}{space 2} .0545041{col 56}{space 1}   -1.51{col 65}{space 3}0.131{col 73}{space 4}-.1893417{col 86}{space 3} .0245137
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}  .150579{col 45}{space 2} .0611322{col 56}{space 1}    2.46{col 65}{space 3}0.014{col 73}{space 4} .0306481{col 86}{space 3} .2705098
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0334696{col 45}{space 2} .0722402{col 56}{space 1}   -0.46{col 65}{space 3}0.643{col 73}{space 4}-.1751925{col 86}{space 3} .1082534
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3994331{col 45}{space 2} .0472981{col 56}{space 1}   -8.45{col 65}{space 3}0.000{col 73}{space 4}-.4922239{col 86}{space 3}-.3066423
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1325155{col 45}{space 2}  .066444{col 56}{space 1}    1.99{col 65}{space 3}0.046{col 73}{space 4} .0021637{col 86}{space 3} .2628673
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2087176{col 45}{space 2} .0914803{col 56}{space 1}   -2.28{col 65}{space 3}0.023{col 73}{space 4}-.3881863{col 86}{space 3}-.0292489
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1228367{col 45}{space 2} .0888647{col 56}{space 1}   -1.38{col 65}{space 3}0.167{col 73}{space 4}-.2971741{col 86}{space 3} .0515007
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0762709{col 45}{space 2} .1059627{col 56}{space 1}   -0.72{col 65}{space 3}0.472{col 73}{space 4}-.2841516{col 86}{space 3} .1316099
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2574217{col 45}{space 2} .0876313{col 56}{space 1}    2.94{col 65}{space 3}0.003{col 73}{space 4}  .085504{col 86}{space 3} .4293394
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1320683{col 45}{space 2} .1152797{col 56}{space 1}    1.15{col 65}{space 3}0.252{col 73}{space 4}-.0940908{col 86}{space 3} .3582274
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9206123{col 45}{space 2} .1469013{col 56}{space 1}    6.27{col 65}{space 3}0.000{col 73}{space 4} .6324171{col 86}{space 3} 1.208808
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,796
                                                {txt}F(1, 1794)        =  {res}    13.43
                                                {txt}Prob > F          = {res}    0.0003
                                                {txt}R-squared         = {res}    0.0076
                                                {txt}Root MSE          =    {res} .49337

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1236302{col 26}{space 2} .0337292{col 37}{space 1}    3.67{col 46}{space 3}0.000{col 54}{space 4} .0574776{col 67}{space 3} .1897829
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4118029{col 26}{space 2} .0125402{col 37}{space 1}   32.84{col 46}{space 3}0.000{col 54}{space 4} .3872078{col 67}{space 3} .4363979
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,288
                                                {txt}F(42, 1245)       =  {res}    20.28
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2565
                                                {txt}Root MSE          =    {res} .43778

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1087809{col 45}{space 2} .0357018{col 56}{space 1}    3.05{col 65}{space 3}0.002{col 73}{space 4} .0387386{col 86}{space 3} .1788232
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0152304{col 45}{space 2} .0263703{col 56}{space 1}   -0.58{col 65}{space 3}0.564{col 73}{space 4}-.0669656{col 86}{space 3} .0365048
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0056149{col 45}{space 2} .0894797{col 56}{space 1}   -0.06{col 65}{space 3}0.950{col 73}{space 4}-.1811626{col 86}{space 3} .1699328
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0073387{col 45}{space 2} .0573505{col 56}{space 1}    0.13{col 65}{space 3}0.898{col 73}{space 4}-.1051757{col 86}{space 3} .1198531
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0216361{col 45}{space 2} .0456026{col 56}{space 1}   -0.47{col 65}{space 3}0.635{col 73}{space 4}-.1111024{col 86}{space 3} .0678303
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0526414{col 45}{space 2} .0433738{col 56}{space 1}   -1.21{col 65}{space 3}0.225{col 73}{space 4}-.1377352{col 86}{space 3} .0324524
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0318182{col 45}{space 2} .0459678{col 56}{space 1}   -0.69{col 65}{space 3}0.489{col 73}{space 4} -.122001{col 86}{space 3} .0583647
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}  .008242{col 45}{space 2} .0542313{col 56}{space 1}    0.15{col 65}{space 3}0.879{col 73}{space 4}-.0981528{col 86}{space 3} .1146367
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0210769{col 45}{space 2} .0739599{col 56}{space 1}   -0.28{col 65}{space 3}0.776{col 73}{space 4}-.1661767{col 86}{space 3} .1240228
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .2120841{col 45}{space 2} .1095135{col 56}{space 1}    1.94{col 65}{space 3}0.053{col 73}{space 4}-.0027673{col 86}{space 3} .4269354
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4377329{col 45}{space 2} .1853431{col 56}{space 1}   -2.36{col 65}{space 3}0.018{col 73}{space 4}-.8013522{col 86}{space 3}-.0741137
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0200657{col 45}{space 2} .2483122{col 56}{space 1}   -0.08{col 65}{space 3}0.936{col 73}{space 4}-.5072223{col 86}{space 3} .4670909
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0005951{col 45}{space 2} .0046422{col 56}{space 1}   -0.13{col 65}{space 3}0.898{col 73}{space 4}-.0097025{col 86}{space 3} .0085123
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} -.000019{col 45}{space 2} .0000483{col 56}{space 1}   -0.39{col 65}{space 3}0.694{col 73}{space 4}-.0001137{col 86}{space 3} .0000758
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0714937{col 45}{space 2} .1060906{col 56}{space 1}   -0.67{col 65}{space 3}0.501{col 73}{space 4}-.2796297{col 86}{space 3} .1366424
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} -.143607{col 45}{space 2} .1071259{col 56}{space 1}   -1.34{col 65}{space 3}0.180{col 73}{space 4}-.3537742{col 86}{space 3} .0665602
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1605353{col 45}{space 2} .1087482{col 56}{space 1}   -1.48{col 65}{space 3}0.140{col 73}{space 4}-.3738852{col 86}{space 3} .0528146
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} -.095902{col 45}{space 2}  .108033{col 56}{space 1}   -0.89{col 65}{space 3}0.375{col 73}{space 4} -.307849{col 86}{space 3} .1160449
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1003165{col 45}{space 2} .1093777{col 56}{space 1}   -0.92{col 65}{space 3}0.359{col 73}{space 4}-.3149015{col 86}{space 3} .1142685
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0046516{col 45}{space 2} .0644335{col 56}{space 1}    0.07{col 65}{space 3}0.942{col 73}{space 4}-.1217586{col 86}{space 3} .1310619
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1223962{col 45}{space 2} .0621294{col 56}{space 1}   -1.97{col 65}{space 3}0.049{col 73}{space 4} -.244286{col 86}{space 3}-.0005063
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1775567{col 45}{space 2}   .06814{col 56}{space 1}   -2.61{col 65}{space 3}0.009{col 73}{space 4}-.3112385{col 86}{space 3}-.0438748
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.1905422{col 45}{space 2} .0636315{col 56}{space 1}   -2.99{col 65}{space 3}0.003{col 73}{space 4}-.3153789{col 86}{space 3}-.0657054
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3795888{col 45}{space 2} .0706171{col 56}{space 1}   -5.38{col 65}{space 3}0.000{col 73}{space 4}-.5181305{col 86}{space 3}-.2410472
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2283036{col 45}{space 2} .0669319{col 56}{space 1}   -3.41{col 65}{space 3}0.001{col 73}{space 4}-.3596154{col 86}{space 3}-.0969917
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0149671{col 45}{space 2} .0695388{col 56}{space 1}   -0.22{col 65}{space 3}0.830{col 73}{space 4}-.1513933{col 86}{space 3} .1214592
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2352058{col 45}{space 2}  .071877{col 56}{space 1}   -3.27{col 65}{space 3}0.001{col 73}{space 4}-.3762193{col 86}{space 3}-.0941923
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1817229{col 45}{space 2} .0779459{col 56}{space 1}   -2.33{col 65}{space 3}0.020{col 73}{space 4}-.3346428{col 86}{space 3} -.028803
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3600367{col 45}{space 2} .0541869{col 56}{space 1}    6.64{col 65}{space 3}0.000{col 73}{space 4}  .253729{col 86}{space 3} .4663444
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0044411{col 45}{space 2}  .071523{col 56}{space 1}    0.06{col 65}{space 3}0.950{col 73}{space 4}-.1358779{col 86}{space 3} .1447601
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}  .044265{col 45}{space 2} .0716518{col 56}{space 1}    0.62{col 65}{space 3}0.537{col 73}{space 4}-.0963066{col 86}{space 3} .1848367
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4427364{col 45}{space 2} .0480549{col 56}{space 1}   -9.21{col 65}{space 3}0.000{col 73}{space 4} -.537014{col 86}{space 3}-.3484589
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0781453{col 45}{space 2}   .05438{col 56}{space 1}   -1.44{col 65}{space 3}0.151{col 73}{space 4}-.1848319{col 86}{space 3} .0285414
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1517384{col 45}{space 2} .0612357{col 56}{space 1}    2.48{col 65}{space 3}0.013{col 73}{space 4} .0316019{col 86}{space 3}  .271875
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0304251{col 45}{space 2} .0719203{col 56}{space 1}   -0.42{col 65}{space 3}0.672{col 73}{space 4}-.1715236{col 86}{space 3} .1106734
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4033692{col 45}{space 2} .0471753{col 56}{space 1}   -8.55{col 65}{space 3}0.000{col 73}{space 4} -.495921{col 86}{space 3}-.3108174
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1325096{col 45}{space 2} .0667778{col 56}{space 1}    1.98{col 65}{space 3}0.047{col 73}{space 4} .0015002{col 86}{space 3} .2635191
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2059477{col 45}{space 2} .0911996{col 56}{space 1}   -2.26{col 65}{space 3}0.024{col 73}{space 4}-.3848696{col 86}{space 3}-.0270258
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.123542{col 45}{space 2}  .089671{col 56}{space 1}   -1.38{col 65}{space 3}0.169{col 73}{space 4}-.2994649{col 86}{space 3} .0523809
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0898781{col 45}{space 2} .1073736{col 56}{space 1}   -0.84{col 65}{space 3}0.403{col 73}{space 4}-.3005312{col 86}{space 3} .1207751
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2682111{col 45}{space 2} .0869189{col 56}{space 1}    3.09{col 65}{space 3}0.002{col 73}{space 4} .0976874{col 86}{space 3} .4387348
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1374779{col 45}{space 2} .1145647{col 56}{space 1}    1.20{col 65}{space 3}0.230{col 73}{space 4}-.0872832{col 86}{space 3}  .362239
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9184542{col 45}{space 2} .1499588{col 56}{space 1}    6.12{col 65}{space 3}0.000{col 73}{space 4} .6242543{col 86}{space 3} 1.212654
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,768
                                                {txt}F(1, 1766)        =  {res}    12.26
                                                {txt}Prob > F          = {res}    0.0005
                                                {txt}R-squared         = {res}    0.0070
                                                {txt}Root MSE          =    {res} .49459

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1206146{col 26}{space 2} .0344536{col 37}{space 1}    3.50{col 46}{space 3}0.000{col 54}{space 4} .0530404{col 67}{space 3} .1881887
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4207077{col 26}{space 2} .0126447{col 37}{space 1}   33.27{col 46}{space 3}0.000{col 54}{space 4} .3959076{col 67}{space 3} .4455078
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,300
                                                {txt}F(42, 1257)       =  {res}    19.92
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2523
                                                {txt}Root MSE          =    {res} .43892

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2}  .086337{col 45}{space 2} .0361327{col 56}{space 1}    2.39{col 65}{space 3}0.017{col 73}{space 4} .0154499{col 86}{space 3} .1572241
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0065364{col 45}{space 2} .0264654{col 56}{space 1}   -0.25{col 65}{space 3}0.805{col 73}{space 4}-.0584576{col 86}{space 3} .0453848
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0559539{col 45}{space 2} .0979324{col 56}{space 1}   -0.57{col 65}{space 3}0.568{col 73}{space 4} -.248083{col 86}{space 3} .1361751
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0070163{col 45}{space 2} .0567412{col 56}{space 1}    0.12{col 65}{space 3}0.902{col 73}{space 4}-.1043017{col 86}{space 3} .1183343
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0337045{col 45}{space 2} .0458309{col 56}{space 1}   -0.74{col 65}{space 3}0.462{col 73}{space 4} -.123618{col 86}{space 3} .0562089
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0571809{col 45}{space 2} .0434435{col 56}{space 1}   -1.32{col 65}{space 3}0.188{col 73}{space 4}-.1424107{col 86}{space 3} .0280489
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0047699{col 45}{space 2} .0455248{col 56}{space 1}   -0.10{col 65}{space 3}0.917{col 73}{space 4}-.0940829{col 86}{space 3} .0845431
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0059667{col 45}{space 2} .0543489{col 56}{space 1}    0.11{col 65}{space 3}0.913{col 73}{space 4}-.1006578{col 86}{space 3} .1125912
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0208079{col 45}{space 2} .0741942{col 56}{space 1}   -0.28{col 65}{space 3}0.779{col 73}{space 4} -.166366{col 86}{space 3} .1247502
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1905228{col 45}{space 2} .1087954{col 56}{space 1}    1.75{col 65}{space 3}0.080{col 73}{space 4}-.0229177{col 86}{space 3} .4039633
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4296396{col 45}{space 2} .1789613{col 56}{space 1}   -2.40{col 65}{space 3}0.017{col 73}{space 4}-.7807354{col 86}{space 3}-.0785438
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0413644{col 45}{space 2} .2096905{col 56}{space 1}    0.20{col 65}{space 3}0.844{col 73}{space 4}-.3700176{col 86}{space 3} .4527464
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} -.001506{col 45}{space 2} .0045967{col 56}{space 1}   -0.33{col 65}{space 3}0.743{col 73}{space 4}-.0105241{col 86}{space 3} .0075121
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-8.53e-06{col 45}{space 2} .0000478{col 56}{space 1}   -0.18{col 65}{space 3}0.858{col 73}{space 4}-.0001022{col 86}{space 3} .0000852
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0222964{col 45}{space 2} .1113318{col 56}{space 1}   -0.20{col 65}{space 3}0.841{col 73}{space 4}-.2407131{col 86}{space 3} .1961203
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} -.095949{col 45}{space 2}  .111851{col 56}{space 1}   -0.86{col 65}{space 3}0.391{col 73}{space 4}-.3153842{col 86}{space 3} .1234863
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1306045{col 45}{space 2} .1136127{col 56}{space 1}   -1.15{col 65}{space 3}0.251{col 73}{space 4} -.353496{col 86}{space 3} .0922869
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0570871{col 45}{space 2} .1127956{col 56}{space 1}   -0.51{col 65}{space 3}0.613{col 73}{space 4}-.2783755{col 86}{space 3} .1642012
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0685124{col 45}{space 2} .1141139{col 56}{space 1}   -0.60{col 65}{space 3}0.548{col 73}{space 4}-.2923871{col 86}{space 3} .1553623
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0023828{col 45}{space 2} .0612644{col 56}{space 1}   -0.04{col 65}{space 3}0.969{col 73}{space 4}-.1225746{col 86}{space 3}  .117809
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1209978{col 45}{space 2} .0593134{col 56}{space 1}   -2.04{col 65}{space 3}0.042{col 73}{space 4}-.2373619{col 86}{space 3}-.0046336
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1811198{col 45}{space 2} .0663226{col 56}{space 1}   -2.73{col 65}{space 3}0.006{col 73}{space 4} -.311235{col 86}{space 3}-.0510045
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2088161{col 45}{space 2} .0610019{col 56}{space 1}   -3.42{col 65}{space 3}0.001{col 73}{space 4}-.3284929{col 86}{space 3}-.0891393
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3817765{col 45}{space 2} .0685853{col 56}{space 1}   -5.57{col 65}{space 3}0.000{col 73}{space 4}-.5163307{col 86}{space 3}-.2472222
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2381649{col 45}{space 2} .0645449{col 56}{space 1}   -3.69{col 65}{space 3}0.000{col 73}{space 4}-.3647926{col 86}{space 3}-.1115372
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0230649{col 45}{space 2} .0690818{col 56}{space 1}   -0.33{col 65}{space 3}0.739{col 73}{space 4}-.1585933{col 86}{space 3} .1124636
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2307522{col 45}{space 2} .0726463{col 56}{space 1}   -3.18{col 65}{space 3}0.002{col 73}{space 4}-.3732734{col 86}{space 3}-.0882309
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1867376{col 45}{space 2} .0778147{col 56}{space 1}   -2.40{col 65}{space 3}0.017{col 73}{space 4}-.3393987{col 86}{space 3}-.0340765
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3638443{col 45}{space 2} .0542898{col 56}{space 1}    6.70{col 65}{space 3}0.000{col 73}{space 4} .2573356{col 86}{space 3}  .470353
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0636386{col 45}{space 2} .0689815{col 56}{space 1}   -0.92{col 65}{space 3}0.356{col 73}{space 4}-.1989702{col 86}{space 3}  .071693
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0397803{col 45}{space 2} .0710867{col 56}{space 1}    0.56{col 65}{space 3}0.576{col 73}{space 4}-.0996813{col 86}{space 3}  .179242
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} -.448169{col 45}{space 2} .0482929{col 56}{space 1}   -9.28{col 65}{space 3}0.000{col 73}{space 4}-.5429126{col 86}{space 3}-.3534254
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0838202{col 45}{space 2} .0543444{col 56}{space 1}   -1.54{col 65}{space 3}0.123{col 73}{space 4} -.190436{col 86}{space 3} .0227955
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1550175{col 45}{space 2} .0608827{col 56}{space 1}    2.55{col 65}{space 3}0.011{col 73}{space 4} .0355746{col 86}{space 3} .2744603
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0315529{col 45}{space 2} .0720759{col 56}{space 1}   -0.44{col 65}{space 3}0.662{col 73}{space 4}-.1729552{col 86}{space 3} .1098494
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4016034{col 45}{space 2} .0474156{col 56}{space 1}   -8.47{col 65}{space 3}0.000{col 73}{space 4}-.4946258{col 86}{space 3} -.308581
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}  .130235{col 45}{space 2} .0664575{col 56}{space 1}    1.96{col 65}{space 3}0.050{col 73}{space 4}-.0001449{col 86}{space 3} .2606148
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2070413{col 45}{space 2} .0906109{col 56}{space 1}   -2.28{col 65}{space 3}0.022{col 73}{space 4}-.3848064{col 86}{space 3}-.0292761
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1266287{col 45}{space 2} .0888453{col 56}{space 1}   -1.43{col 65}{space 3}0.154{col 73}{space 4}-.3009301{col 86}{space 3} .0476727
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0810004{col 45}{space 2} .1061264{col 56}{space 1}   -0.76{col 65}{space 3}0.445{col 73}{space 4}-.2892048{col 86}{space 3}  .127204
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2587371{col 45}{space 2} .0882273{col 56}{space 1}    2.93{col 65}{space 3}0.003{col 73}{space 4} .0856482{col 86}{space 3}  .431826
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1453301{col 45}{space 2} .1161063{col 56}{space 1}    1.25{col 65}{space 3}0.211{col 73}{space 4}-.0824534{col 86}{space 3} .3731136
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9023225{col 45}{space 2} .1536927{col 56}{space 1}    5.87{col 65}{space 3}0.000{col 73}{space 4}    .6008{col 86}{space 3} 1.203845
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,784
                                                {txt}F(1, 1782)        =  {res}     8.85
                                                {txt}Prob > F          = {res}    0.0030
                                                {txt}R-squared         = {res}    0.0050
                                                {txt}Root MSE          =    {res} .49493

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1026144{col 26}{space 2} .0344971{col 37}{space 1}    2.97{col 46}{space 3}0.003{col 54}{space 4} .0349553{col 67}{space 3} .1702735
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .422179{col 26}{space 2} .0125848{col 37}{space 1}   33.55{col 46}{space 3}0.000{col 54}{space 4} .3974965{col 67}{space 3} .4468615
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,302
                                                {txt}F(42, 1259)       =  {res}    19.42
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2496
                                                {txt}Root MSE          =    {res} .43963

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0930416{col 45}{space 2} .0359255{col 56}{space 1}    2.59{col 65}{space 3}0.010{col 73}{space 4} .0225612{col 86}{space 3} .1635221
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0161176{col 45}{space 2} .0264939{col 56}{space 1}   -0.61{col 65}{space 3}0.543{col 73}{space 4}-.0680947{col 86}{space 3} .0358595
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0061431{col 45}{space 2}  .090693{col 56}{space 1}    0.07{col 65}{space 3}0.946{col 73}{space 4} -.171783{col 86}{space 3} .1840692
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0095437{col 45}{space 2} .0582036{col 56}{space 1}    0.16{col 65}{space 3}0.870{col 73}{space 4} -.104643{col 86}{space 3} .1237303
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0125394{col 45}{space 2} .0460153{col 56}{space 1}   -0.27{col 65}{space 3}0.785{col 73}{space 4}-.1028145{col 86}{space 3} .0777357
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0327549{col 45}{space 2} .0433466{col 56}{space 1}   -0.76{col 65}{space 3}0.450{col 73}{space 4}-.1177946{col 86}{space 3} .0522847
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0148207{col 45}{space 2} .0462312{col 56}{space 1}   -0.32{col 65}{space 3}0.749{col 73}{space 4}-.1055194{col 86}{space 3} .0758781
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0298144{col 45}{space 2} .0539765{col 56}{space 1}    0.55{col 65}{space 3}0.581{col 73}{space 4}-.0760795{col 86}{space 3} .1357083
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0033527{col 45}{space 2} .0740726{col 56}{space 1}   -0.05{col 65}{space 3}0.964{col 73}{space 4} -.148672{col 86}{space 3} .1419666
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1589456{col 45}{space 2} .1135689{col 56}{space 1}    1.40{col 65}{space 3}0.162{col 73}{space 4}-.0638596{col 86}{space 3} .3817509
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4042488{col 45}{space 2}  .178366{col 56}{space 1}   -2.27{col 65}{space 3}0.024{col 73}{space 4}-.7541761{col 86}{space 3}-.0543214
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0410491{col 45}{space 2} .2089189{col 56}{space 1}    0.20{col 65}{space 3}0.844{col 73}{space 4}-.3688185{col 86}{space 3} .4509167
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0011548{col 45}{space 2} .0047196{col 56}{space 1}   -0.24{col 65}{space 3}0.807{col 73}{space 4}-.0104139{col 86}{space 3} .0081043
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000147{col 45}{space 2} .0000491{col 56}{space 1}   -0.30{col 65}{space 3}0.764{col 73}{space 4}-.0001111{col 86}{space 3} .0000816
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} -.068305{col 45}{space 2} .1062523{col 56}{space 1}   -0.64{col 65}{space 3}0.520{col 73}{space 4}-.2767561{col 86}{space 3}  .140146
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1463718{col 45}{space 2} .1069526{col 56}{space 1}   -1.37{col 65}{space 3}0.171{col 73}{space 4}-.3561968{col 86}{space 3} .0634532
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1679002{col 45}{space 2} .1085743{col 56}{space 1}   -1.55{col 65}{space 3}0.122{col 73}{space 4}-.3809068{col 86}{space 3} .0451063
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2} -.094379{col 45}{space 2} .1077936{col 56}{space 1}   -0.88{col 65}{space 3}0.381{col 73}{space 4}-.3058538{col 86}{space 3} .1170958
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1209379{col 45}{space 2} .1091752{col 56}{space 1}   -1.11{col 65}{space 3}0.268{col 73}{space 4}-.3351233{col 86}{space 3} .0932474
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0084189{col 45}{space 2}  .063603{col 56}{space 1}    0.13{col 65}{space 3}0.895{col 73}{space 4}-.1163607{col 86}{space 3} .1331984
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1215638{col 45}{space 2} .0614308{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4}-.2420819{col 86}{space 3}-.0010458
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1541286{col 45}{space 2} .0679617{col 56}{space 1}   -2.27{col 65}{space 3}0.024{col 73}{space 4}-.2874592{col 86}{space 3} -.020798
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2105597{col 45}{space 2} .0637563{col 56}{space 1}   -3.30{col 65}{space 3}0.001{col 73}{space 4}-.3356399{col 86}{space 3}-.0854795
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3747366{col 45}{space 2} .0704544{col 56}{space 1}   -5.32{col 65}{space 3}0.000{col 73}{space 4}-.5129575{col 86}{space 3}-.2365156
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2291318{col 45}{space 2} .0669472{col 56}{space 1}   -3.42{col 65}{space 3}0.001{col 73}{space 4}-.3604722{col 86}{space 3}-.0977914
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0214035{col 45}{space 2} .0691424{col 56}{space 1}   -0.31{col 65}{space 3}0.757{col 73}{space 4}-.1570505{col 86}{space 3} .1142436
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}  -.23286{col 45}{space 2}  .072673{col 56}{space 1}   -3.20{col 65}{space 3}0.001{col 73}{space 4}-.3754334{col 86}{space 3}-.0902865
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1862831{col 45}{space 2} .0775891{col 56}{space 1}   -2.40{col 65}{space 3}0.016{col 73}{space 4}-.3385013{col 86}{space 3}-.0340649
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3626891{col 45}{space 2} .0540706{col 56}{space 1}    6.71{col 65}{space 3}0.000{col 73}{space 4} .2566107{col 86}{space 3} .4687675
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0606319{col 45}{space 2} .0688453{col 56}{space 1}   -0.88{col 65}{space 3}0.379{col 73}{space 4} -.195696{col 86}{space 3} .0744322
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0000494{col 45}{space 2} .0707857{col 56}{space 1}    0.00{col 65}{space 3}0.999{col 73}{space 4}-.1388215{col 86}{space 3} .1389204
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4440308{col 45}{space 2} .0482786{col 56}{space 1}   -9.20{col 65}{space 3}0.000{col 73}{space 4}-.5387461{col 86}{space 3}-.3493155
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0819228{col 45}{space 2} .0543381{col 56}{space 1}   -1.51{col 65}{space 3}0.132{col 73}{space 4}-.1885259{col 86}{space 3} .0246803
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1533376{col 45}{space 2} .0617487{col 56}{space 1}    2.48{col 65}{space 3}0.013{col 73}{space 4} .0321959{col 86}{space 3} .2744793
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0303858{col 45}{space 2} .0724005{col 56}{space 1}   -0.42{col 65}{space 3}0.675{col 73}{space 4}-.1724248{col 86}{space 3} .1116532
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4008557{col 45}{space 2} .0472943{col 56}{space 1}   -8.48{col 65}{space 3}0.000{col 73}{space 4}-.4936401{col 86}{space 3}-.3080713
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1326418{col 45}{space 2} .0664832{col 56}{space 1}    2.00{col 65}{space 3}0.046{col 73}{space 4} .0022117{col 86}{space 3} .2630719
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2021894{col 45}{space 2} .0911277{col 56}{space 1}   -2.22{col 65}{space 3}0.027{col 73}{space 4}-.3809682{col 86}{space 3}-.0234105
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1195479{col 45}{space 2} .0887344{col 56}{space 1}   -1.35{col 65}{space 3}0.178{col 73}{space 4}-.2936314{col 86}{space 3} .0545356
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0717746{col 45}{space 2} .1053897{col 56}{space 1}   -0.68{col 65}{space 3}0.496{col 73}{space 4}-.2785333{col 86}{space 3} .1349842
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2453008{col 45}{space 2} .0872701{col 56}{space 1}    2.81{col 65}{space 3}0.005{col 73}{space 4}   .07409{col 86}{space 3} .4165116
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .112668{col 45}{space 2} .1156438{col 56}{space 1}    0.97{col 65}{space 3}0.330{col 73}{space 4}-.1142079{col 86}{space 3} .3395438
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9318536{col 45}{space 2} .1491242{col 56}{space 1}    6.25{col 65}{space 3}0.000{col 73}{space 4} .6392944{col 86}{space 3} 1.224413
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,772
                                                {txt}F(1, 1770)        =  {res}    10.62
                                                {txt}Prob > F          = {res}    0.0011
                                                {txt}R-squared         = {res}    0.0061
                                                {txt}Root MSE          =    {res} .49469

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1119754{col 26}{space 2} .0343661{col 37}{space 1}    3.26{col 46}{space 3}0.001{col 54}{space 4}  .044573{col 67}{space 3} .1793777
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4208115{col 26}{space 2} .0126368{col 37}{space 1}   33.30{col 46}{space 3}0.000{col 54}{space 4} .3960269{col 67}{space 3} .4455962
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,219
                                                {txt}{help j_robustsingular:F(41, 1176) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.2157
                                                {txt}Root MSE          =    {res} .45057

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0949424{col 45}{space 2} .0356312{col 56}{space 1}    2.66{col 65}{space 3}0.008{col 73}{space 4} .0250345{col 86}{space 3} .1648503
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0226397{col 45}{space 2}  .027848{col 56}{space 1}   -0.81{col 65}{space 3}0.416{col 73}{space 4}-.0772771{col 86}{space 3} .0319977
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0438937{col 45}{space 2} .0866971{col 56}{space 1}   -0.51{col 65}{space 3}0.613{col 73}{space 4}-.2139919{col 86}{space 3} .1262045
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0109203{col 45}{space 2}  .061469{col 56}{space 1}   -0.18{col 65}{space 3}0.859{col 73}{space 4}-.1315216{col 86}{space 3} .1096809
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0405931{col 45}{space 2} .0475101{col 56}{space 1}   -0.85{col 65}{space 3}0.393{col 73}{space 4}-.1338072{col 86}{space 3}  .052621
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0602595{col 45}{space 2} .0456941{col 56}{space 1}   -1.32{col 65}{space 3}0.188{col 73}{space 4}-.1499106{col 86}{space 3} .0293917
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0345161{col 45}{space 2} .0487765{col 56}{space 1}   -0.71{col 65}{space 3}0.479{col 73}{space 4}-.1302148{col 86}{space 3} .0611826
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0076298{col 45}{space 2} .0591814{col 56}{space 1}    0.13{col 65}{space 3}0.897{col 73}{space 4}-.1084831{col 86}{space 3} .1237426
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0170365{col 45}{space 2} .0831878{col 56}{space 1}   -0.20{col 65}{space 3}0.838{col 73}{space 4}-.1802497{col 86}{space 3} .1461767
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1286993{col 45}{space 2} .1145688{col 56}{space 1}    1.12{col 65}{space 3}0.262{col 73}{space 4}-.0960828{col 86}{space 3} .3534814
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.6555693{col 45}{space 2} .0814145{col 56}{space 1}   -8.05{col 65}{space 3}0.000{col 73}{space 4}-.8153033{col 86}{space 3}-.4958353
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0187231{col 45}{space 2} .2117325{col 56}{space 1}    0.09{col 65}{space 3}0.930{col 73}{space 4}-.3966926{col 86}{space 3} .4341388
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0000751{col 45}{space 2} .0049444{col 56}{space 1}    0.02{col 65}{space 3}0.988{col 73}{space 4}-.0096257{col 86}{space 3}  .009776
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000277{col 45}{space 2} .0000515{col 56}{space 1}   -0.54{col 65}{space 3}0.590{col 73}{space 4}-.0001288{col 86}{space 3} .0000733
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0795305{col 45}{space 2} .1166409{col 56}{space 1}   -0.68{col 65}{space 3}0.495{col 73}{space 4}-.3083781{col 86}{space 3} .1493171
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1702828{col 45}{space 2} .1185209{col 56}{space 1}   -1.44{col 65}{space 3}0.151{col 73}{space 4}-.4028188{col 86}{space 3} .0622532
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2066246{col 45}{space 2} .1201931{col 56}{space 1}   -1.72{col 65}{space 3}0.086{col 73}{space 4}-.4424415{col 86}{space 3} .0291923
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1207302{col 45}{space 2} .1199005{col 56}{space 1}   -1.01{col 65}{space 3}0.314{col 73}{space 4}-.3559731{col 86}{space 3} .1145126
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1406936{col 45}{space 2}  .121251{col 56}{space 1}   -1.16{col 65}{space 3}0.246{col 73}{space 4} -.378586{col 86}{space 3} .0971988
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0301799{col 45}{space 2} .0636215{col 56}{space 1}    0.47{col 65}{space 3}0.635{col 73}{space 4}-.0946445{col 86}{space 3} .1550043
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1054063{col 45}{space 2} .0629326{col 56}{space 1}   -1.67{col 65}{space 3}0.094{col 73}{space 4} -.228879{col 86}{space 3} .0180663
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1536819{col 45}{space 2} .0691532{col 56}{space 1}   -2.22{col 65}{space 3}0.026{col 73}{space 4}-.2893593{col 86}{space 3}-.0180045
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2209995{col 45}{space 2} .0645257{col 56}{space 1}   -3.42{col 65}{space 3}0.001{col 73}{space 4} -.347598{col 86}{space 3}-.0944011
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3624883{col 45}{space 2} .0709257{col 56}{space 1}   -5.11{col 65}{space 3}0.000{col 73}{space 4}-.5016434{col 86}{space 3}-.2233332
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1797177{col 45}{space 2} .0820779{col 56}{space 1}   -2.19{col 65}{space 3}0.029{col 73}{space 4}-.3407532{col 86}{space 3}-.0186822
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0171891{col 45}{space 2} .0696233{col 56}{space 1}   -0.25{col 65}{space 3}0.805{col 73}{space 4}-.1537887{col 86}{space 3} .1194106
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2218191{col 45}{space 2} .0729058{col 56}{space 1}   -3.04{col 65}{space 3}0.002{col 73}{space 4} -.364859{col 86}{space 3}-.0787791
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} -.186584{col 45}{space 2} .0779774{col 56}{space 1}   -2.39{col 65}{space 3}0.017{col 73}{space 4}-.3395743{col 86}{space 3}-.0335936
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3733143{col 45}{space 2} .0542976{col 56}{space 1}    6.88{col 65}{space 3}0.000{col 73}{space 4} .2667833{col 86}{space 3} .4798453
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0597981{col 45}{space 2}  .068707{col 56}{space 1}   -0.87{col 65}{space 3}0.384{col 73}{space 4}-.1946001{col 86}{space 3}  .075004
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0036031{col 45}{space 2} .0710522{col 56}{space 1}    0.05{col 65}{space 3}0.960{col 73}{space 4}   -.1358{col 86}{space 3} .1430063
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0509235{col 45}{space 2} .0719009{col 56}{space 1}    0.71{col 65}{space 3}0.479{col 73}{space 4}-.0901448{col 86}{space 3} .1919918
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0806545{col 45}{space 2} .0545649{col 56}{space 1}   -1.48{col 65}{space 3}0.140{col 73}{space 4}-.1877099{col 86}{space 3} .0264008
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}  .160148{col 45}{space 2} .0623087{col 56}{space 1}    2.57{col 65}{space 3}0.010{col 73}{space 4} .0378993{col 86}{space 3} .2823967
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0307222{col 45}{space 2} .0725939{col 56}{space 1}   -0.42{col 65}{space 3}0.672{col 73}{space 4}-.1731502{col 86}{space 3} .1117058
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4069234{col 45}{space 2} .0507393{col 56}{space 1}   -8.02{col 65}{space 3}0.000{col 73}{space 4} -.506473{col 86}{space 3}-.3073737
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1328329{col 45}{space 2} .0661101{col 56}{space 1}    2.01{col 65}{space 3}0.045{col 73}{space 4}  .003126{col 86}{space 3} .2625399
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2070001{col 45}{space 2} .0908943{col 56}{space 1}   -2.28{col 65}{space 3}0.023{col 73}{space 4}-.3853331{col 86}{space 3} -.028667
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1136827{col 45}{space 2} .0890557{col 56}{space 1}   -1.28{col 65}{space 3}0.202{col 73}{space 4}-.2884084{col 86}{space 3} .0610431
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0579514{col 45}{space 2} .1052127{col 56}{space 1}   -0.55{col 65}{space 3}0.582{col 73}{space 4} -.264377{col 86}{space 3} .1484741
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2530203{col 45}{space 2} .0873845{col 56}{space 1}    2.90{col 65}{space 3}0.004{col 73}{space 4} .0815734{col 86}{space 3} .4244672
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .125008{col 45}{space 2}  .115173{col 56}{space 1}    1.09{col 65}{space 3}0.278{col 73}{space 4}-.1009595{col 86}{space 3} .3509755
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9429586{col 45}{space 2} .1565331{col 56}{space 1}    6.02{col 65}{space 3}0.000{col 73}{space 4} .6358431{col 86}{space 3} 1.250074
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,585
                                                {txt}F(1, 1583)        =  {res}     3.66
                                                {txt}Prob > F          = {res}    0.0560
                                                {txt}R-squared         = {res}    0.0023
                                                {txt}Root MSE          =    {res} .49974

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .0658009{col 26}{space 2} .0344039{col 37}{space 1}    1.91{col 46}{space 3}0.056{col 54}{space 4}-.0016811{col 67}{space 3} .1332829
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4906507{col 26}{space 2} .0136805{col 37}{space 1}   35.86{col 46}{space 3}0.000{col 54}{space 4} .4638169{col 67}{space 3} .5174845
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,231
                                                {txt}F(42, 1188)       =  {res}    20.35
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2692
                                                {txt}Root MSE          =    {res} .43467

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1061399{col 45}{space 2} .0356579{col 56}{space 1}    2.98{col 65}{space 3}0.003{col 73}{space 4} .0361804{col 86}{space 3} .1760994
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0111724{col 45}{space 2} .0270716{col 56}{space 1}   -0.41{col 65}{space 3}0.680{col 73}{space 4}-.0642859{col 86}{space 3}  .041941
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0677789{col 45}{space 2} .0970015{col 56}{space 1}    0.70{col 65}{space 3}0.485{col 73}{space 4}-.1225344{col 86}{space 3} .2580922
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0558578{col 45}{space 2} .0584535{col 56}{space 1}    0.96{col 65}{space 3}0.339{col 73}{space 4}-.0588259{col 86}{space 3} .1705414
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0323555{col 45}{space 2} .0460688{col 56}{space 1}   -0.70{col 65}{space 3}0.483{col 73}{space 4}-.1227407{col 86}{space 3} .0580298
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0106506{col 45}{space 2} .0437771{col 56}{space 1}   -0.24{col 65}{space 3}0.808{col 73}{space 4}-.0965397{col 86}{space 3} .0752384
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0040309{col 45}{space 2} .0461905{col 56}{space 1}    0.09{col 65}{space 3}0.930{col 73}{space 4}-.0865931{col 86}{space 3} .0946549
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0369969{col 45}{space 2} .0549496{col 56}{space 1}    0.67{col 65}{space 3}0.501{col 73}{space 4}-.0708122{col 86}{space 3} .1448061
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0009398{col 45}{space 2}  .075375{col 56}{space 1}   -0.01{col 65}{space 3}0.990{col 73}{space 4}-.1488228{col 86}{space 3} .1469431
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1566595{col 45}{space 2} .1154458{col 56}{space 1}    1.36{col 65}{space 3}0.175{col 73}{space 4}-.0698408{col 86}{space 3} .3831599
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4124089{col 45}{space 2} .1689079{col 56}{space 1}   -2.44{col 65}{space 3}0.015{col 73}{space 4}-.7437998{col 86}{space 3}-.0810179
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0681666{col 45}{space 2} .2217799{col 56}{space 1}   -0.31{col 65}{space 3}0.759{col 73}{space 4}-.5032906{col 86}{space 3} .3669574
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0010706{col 45}{space 2}   .00472{col 56}{space 1}   -0.23{col 65}{space 3}0.821{col 73}{space 4} -.010331{col 86}{space 3} .0081898
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-9.21e-06{col 45}{space 2} .0000492{col 56}{space 1}   -0.19{col 65}{space 3}0.852{col 73}{space 4}-.0001058{col 86}{space 3} .0000874
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0603138{col 45}{space 2}  .105369{col 56}{space 1}   -0.57{col 65}{space 3}0.567{col 73}{space 4}-.2670439{col 86}{space 3} .1464164
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1859363{col 45}{space 2} .1065271{col 56}{space 1}   -1.75{col 65}{space 3}0.081{col 73}{space 4}-.3949384{col 86}{space 3} .0230659
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1791511{col 45}{space 2} .1081878{col 56}{space 1}   -1.66{col 65}{space 3}0.098{col 73}{space 4}-.3914116{col 86}{space 3} .0331094
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0995892{col 45}{space 2}  .107495{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.3104905{col 86}{space 3}  .111312
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1077309{col 45}{space 2} .1086636{col 56}{space 1}   -0.99{col 65}{space 3}0.322{col 73}{space 4}-.3209248{col 86}{space 3} .1054629
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0128485{col 45}{space 2} .0608414{col 56}{space 1}   -0.21{col 65}{space 3}0.833{col 73}{space 4} -.132217{col 86}{space 3} .1065201
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1316762{col 45}{space 2} .0590823{col 56}{space 1}   -2.23{col 65}{space 3}0.026{col 73}{space 4}-.2475936{col 86}{space 3}-.0157588
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.2244018{col 45}{space 2} .0659802{col 56}{space 1}   -3.40{col 65}{space 3}0.001{col 73}{space 4}-.3538525{col 86}{space 3}-.0949511
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2516094{col 45}{space 2} .0608374{col 56}{space 1}   -4.14{col 65}{space 3}0.000{col 73}{space 4}-.3709701{col 86}{space 3}-.1322486
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3753964{col 45}{space 2}  .073206{col 56}{space 1}   -5.13{col 65}{space 3}0.000{col 73}{space 4}-.5190238{col 86}{space 3} -.231769
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2698941{col 45}{space 2} .0646873{col 56}{space 1}   -4.17{col 65}{space 3}0.000{col 73}{space 4} -.396808{col 86}{space 3}-.1429801
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0443788{col 45}{space 2} .0701359{col 56}{space 1}   -0.63{col 65}{space 3}0.527{col 73}{space 4}-.1819828{col 86}{space 3} .0932252
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2199862{col 45}{space 2} .0732487{col 56}{space 1}   -3.00{col 65}{space 3}0.003{col 73}{space 4}-.3636975{col 86}{space 3}-.0762748
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.2160477{col 45}{space 2} .0787224{col 56}{space 1}   -2.74{col 65}{space 3}0.006{col 73}{space 4}-.3704982{col 86}{space 3}-.0615972
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3630697{col 45}{space 2} .0550127{col 56}{space 1}    6.60{col 65}{space 3}0.000{col 73}{space 4} .2551368{col 86}{space 3} .4710026
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0690588{col 45}{space 2} .0688193{col 56}{space 1}   -1.00{col 65}{space 3}0.316{col 73}{space 4}-.2040798{col 86}{space 3} .0659622
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0038871{col 45}{space 2} .0708247{col 56}{space 1}    0.05{col 65}{space 3}0.956{col 73}{space 4}-.1350684{col 86}{space 3} .1428425
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0430638{col 45}{space 2} .0711348{col 56}{space 1}    0.61{col 65}{space 3}0.545{col 73}{space 4}-.0965001{col 86}{space 3} .1826276
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4462654{col 45}{space 2} .0484489{col 56}{space 1}   -9.21{col 65}{space 3}0.000{col 73}{space 4}-.5413204{col 86}{space 3}-.3512104
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1463407{col 45}{space 2} .0609126{col 56}{space 1}    2.40{col 65}{space 3}0.016{col 73}{space 4} .0268324{col 86}{space 3} .2658489
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0362072{col 45}{space 2} .0719712{col 56}{space 1}   -0.50{col 65}{space 3}0.615{col 73}{space 4} -.177412{col 86}{space 3} .1049977
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3927278{col 45}{space 2}  .047484{col 56}{space 1}   -8.27{col 65}{space 3}0.000{col 73}{space 4}-.4858896{col 86}{space 3} -.299566
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1202507{col 45}{space 2}  .066323{col 56}{space 1}    1.81{col 65}{space 3}0.070{col 73}{space 4}-.0098725{col 86}{space 3} .2503739
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2219099{col 45}{space 2} .0910607{col 56}{space 1}   -2.44{col 65}{space 3}0.015{col 73}{space 4}-.4005676{col 86}{space 3}-.0432522
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1225487{col 45}{space 2} .0882917{col 56}{space 1}   -1.39{col 65}{space 3}0.165{col 73}{space 4}-.2957739{col 86}{space 3} .0506764
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0716443{col 45}{space 2} .1056358{col 56}{space 1}   -0.68{col 65}{space 3}0.498{col 73}{space 4}-.2788978{col 86}{space 3} .1356092
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2920295{col 45}{space 2} .0893201{col 56}{space 1}    3.27{col 65}{space 3}0.001{col 73}{space 4} .1167867{col 86}{space 3} .4672722
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1542586{col 45}{space 2} .1159715{col 56}{space 1}    1.33{col 65}{space 3}0.184{col 73}{space 4}-.0732731{col 86}{space 3} .3817903
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9380532{col 45}{space 2} .1480007{col 56}{space 1}    6.34{col 65}{space 3}0.000{col 73}{space 4} .6476814{col 86}{space 3} 1.228425
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,706
                                                {txt}F(1, 1704)        =  {res}    10.17
                                                {txt}Prob > F          = {res}    0.0015
                                                {txt}R-squared         = {res}    0.0060
                                                {txt}Root MSE          =    {res} .49521

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1108886{col 26}{space 2} .0347663{col 37}{space 1}    3.19{col 46}{space 3}0.001{col 54}{space 4} .0426994{col 67}{space 3} .1790778
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4246762{col 26}{space 2} .0129129{col 37}{space 1}   32.89{col 46}{space 3}0.000{col 54}{space 4} .3993493{col 67}{space 3} .4500031
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,291
                                                {txt}{help j_robustsingular:F(41, 1248) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.2391
                                                {txt}Root MSE          =    {res} .44228

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0886735{col 45}{space 2} .0365725{col 56}{space 1}    2.42{col 65}{space 3}0.015{col 73}{space 4} .0169232{col 86}{space 3} .1604238
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0161217{col 45}{space 2} .0268579{col 56}{space 1}   -0.60{col 65}{space 3}0.548{col 73}{space 4}-.0688134{col 86}{space 3}   .03657
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0046223{col 45}{space 2} .0965992{col 56}{space 1}    0.05{col 65}{space 3}0.962{col 73}{space 4}-.1848926{col 86}{space 3} .1941371
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0009543{col 45}{space 2} .0594583{col 56}{space 1}   -0.02{col 65}{space 3}0.987{col 73}{space 4}-.1176036{col 86}{space 3}  .115695
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0422093{col 45}{space 2} .0463866{col 56}{space 1}   -0.91{col 65}{space 3}0.363{col 73}{space 4}-.1332137{col 86}{space 3} .0487951
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0508867{col 45}{space 2} .0439613{col 56}{space 1}   -1.16{col 65}{space 3}0.247{col 73}{space 4}-.1371328{col 86}{space 3} .0353595
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0318779{col 45}{space 2} .0462092{col 56}{space 1}   -0.69{col 65}{space 3}0.490{col 73}{space 4}-.1225341{col 86}{space 3} .0587784
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0017912{col 45}{space 2} .0541896{col 56}{space 1}    0.03{col 65}{space 3}0.974{col 73}{space 4}-.1045217{col 86}{space 3}  .108104
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0408705{col 45}{space 2} .0745599{col 56}{space 1}   -0.55{col 65}{space 3}0.584{col 73}{space 4}-.1871471{col 86}{space 3} .1054061
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}  .144433{col 45}{space 2} .1098922{col 56}{space 1}    1.31{col 65}{space 3}0.189{col 73}{space 4}-.0711609{col 86}{space 3} .3600268
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.1850405{col 45}{space 2} .0570354{col 56}{space 1}   -3.24{col 65}{space 3}0.001{col 73}{space 4}-.2969364{col 86}{space 3}-.0731446
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0056606{col 45}{space 2} .2098508{col 56}{space 1}    0.03{col 65}{space 3}0.978{col 73}{space 4}-.4060386{col 86}{space 3} .4173599
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0003618{col 45}{space 2} .0045989{col 56}{space 1}   -0.08{col 65}{space 3}0.937{col 73}{space 4}-.0093842{col 86}{space 3} .0086606
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000189{col 45}{space 2} .0000477{col 56}{space 1}   -0.40{col 65}{space 3}0.692{col 73}{space 4}-.0001126{col 86}{space 3} .0000747
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1149666{col 45}{space 2}  .103061{col 56}{space 1}   -1.12{col 65}{space 3}0.265{col 73}{space 4}-.3171586{col 86}{space 3} .0872253
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1810628{col 45}{space 2} .1034466{col 56}{space 1}   -1.75{col 65}{space 3}0.080{col 73}{space 4}-.3840113{col 86}{space 3} .0218856
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.2078436{col 45}{space 2} .1048315{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4} -.413509{col 86}{space 3}-.0021782
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1379849{col 45}{space 2} .1041158{col 56}{space 1}   -1.33{col 65}{space 3}0.185{col 73}{space 4}-.3422462{col 86}{space 3} .0662765
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1521425{col 45}{space 2} .1054238{col 56}{space 1}   -1.44{col 65}{space 3}0.149{col 73}{space 4}-.3589699{col 86}{space 3} .0546848
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0346877{col 45}{space 2} .0670324{col 56}{space 1}    0.52{col 65}{space 3}0.605{col 73}{space 4}-.0968208{col 86}{space 3} .1661963
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1149658{col 45}{space 2} .0653516{col 56}{space 1}   -1.76{col 65}{space 3}0.079{col 73}{space 4}-.2431769{col 86}{space 3} .0132452
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1263864{col 45}{space 2} .0710311{col 56}{space 1}   -1.78{col 65}{space 3}0.075{col 73}{space 4}-.2657399{col 86}{space 3} .0129672
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2072568{col 45}{space 2} .0673704{col 56}{space 1}   -3.08{col 65}{space 3}0.002{col 73}{space 4}-.3394285{col 86}{space 3} -.075085
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.362214{col 45}{space 2}  .073108{col 56}{space 1}   -4.95{col 65}{space 3}0.000{col 73}{space 4}-.5056421{col 86}{space 3}-.2187859
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2160757{col 45}{space 2} .0699618{col 56}{space 1}   -3.09{col 65}{space 3}0.002{col 73}{space 4}-.3533315{col 86}{space 3}-.0788199
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0151828{col 45}{space 2} .0693349{col 56}{space 1}   -0.22{col 65}{space 3}0.827{col 73}{space 4}-.1512086{col 86}{space 3}  .120843
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2267632{col 45}{space 2} .0731675{col 56}{space 1}   -3.10{col 65}{space 3}0.002{col 73}{space 4}-.3703081{col 86}{space 3}-.0832183
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1795808{col 45}{space 2} .0777703{col 56}{space 1}   -2.31{col 65}{space 3}0.021{col 73}{space 4}-.3321558{col 86}{space 3}-.0270058
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3719087{col 45}{space 2} .0540858{col 56}{space 1}    6.88{col 65}{space 3}0.000{col 73}{space 4} .2657996{col 86}{space 3} .4780178
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0557857{col 45}{space 2} .0686632{col 56}{space 1}   -0.81{col 65}{space 3}0.417{col 73}{space 4}-.1904938{col 86}{space 3} .0789224
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0014139{col 45}{space 2}  .070654{col 56}{space 1}   -0.02{col 65}{space 3}0.984{col 73}{space 4}-.1400277{col 86}{space 3}    .1372
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0508133{col 45}{space 2} .0718955{col 56}{space 1}    0.71{col 65}{space 3}0.480{col 73}{space 4}-.0902361{col 86}{space 3} .1918628
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4395739{col 45}{space 2} .0485073{col 56}{space 1}   -9.06{col 65}{space 3}0.000{col 73}{space 4}-.5347387{col 86}{space 3} -.344409
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} -.080327{col 45}{space 2}  .054333{col 56}{space 1}   -1.48{col 65}{space 3}0.140{col 73}{space 4}-.1869211{col 86}{space 3} .0262671
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0315033{col 45}{space 2} .0726876{col 56}{space 1}   -0.43{col 65}{space 3}0.665{col 73}{space 4}-.1741067{col 86}{space 3} .1111002
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3988444{col 45}{space 2} .0471939{col 56}{space 1}   -8.45{col 65}{space 3}0.000{col 73}{space 4}-.4914325{col 86}{space 3}-.3062562
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1384191{col 45}{space 2} .0661897{col 56}{space 1}    2.09{col 65}{space 3}0.037{col 73}{space 4} .0085637{col 86}{space 3} .2682744
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2004815{col 45}{space 2} .0916251{col 56}{space 1}   -2.19{col 65}{space 3}0.029{col 73}{space 4}-.3802377{col 86}{space 3}-.0207253
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1120401{col 45}{space 2} .0889481{col 56}{space 1}   -1.26{col 65}{space 3}0.208{col 73}{space 4}-.2865444{col 86}{space 3} .0624643
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0621275{col 45}{space 2}  .105638{col 56}{space 1}   -0.59{col 65}{space 3}0.557{col 73}{space 4}-.2693751{col 86}{space 3} .1451201
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2281942{col 45}{space 2}  .087265{col 56}{space 1}    2.61{col 65}{space 3}0.009{col 73}{space 4} .0569919{col 86}{space 3} .3993965
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .103027{col 45}{space 2}  .115148{col 56}{space 1}    0.89{col 65}{space 3}0.371{col 73}{space 4}-.1228779{col 86}{space 3}  .328932
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9453892{col 45}{space 2} .1464296{col 56}{space 1}    6.46{col 65}{space 3}0.000{col 73}{space 4} .6581139{col 86}{space 3} 1.232665
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,775
                                                {txt}F(1, 1773)        =  {res}     9.28
                                                {txt}Prob > F          = {res}    0.0024
                                                {txt}R-squared         = {res}    0.0053
                                                {txt}Root MSE          =    {res} .49402

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}  .105136{col 26}{space 2} .0345117{col 37}{space 1}    3.05{col 46}{space 3}0.002{col 54}{space 4} .0374481{col 67}{space 3}  .172824
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4155251{col 26}{space 2} .0125938{col 37}{space 1}   32.99{col 46}{space 3}0.000{col 54}{space 4} .3908249{col 67}{space 3} .4402253
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,294
                                                {txt}F(42, 1251)       =  {res}    20.18
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2593
                                                {txt}Root MSE          =    {res} .43699

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2}  .113872{col 45}{space 2} .0347571{col 56}{space 1}    3.28{col 65}{space 3}0.001{col 73}{space 4} .0456834{col 86}{space 3} .1820606
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0130444{col 45}{space 2} .0264253{col 56}{space 1}   -0.49{col 65}{space 3}0.622{col 73}{space 4}-.0648871{col 86}{space 3} .0387983
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0093725{col 45}{space 2} .0914776{col 56}{space 1}    0.10{col 65}{space 3}0.918{col 73}{space 4}-.1700939{col 86}{space 3} .1888389
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} -.005717{col 45}{space 2} .0582536{col 56}{space 1}   -0.10{col 65}{space 3}0.922{col 73}{space 4}-.1200025{col 86}{space 3} .1085686
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0436121{col 45}{space 2} .0455108{col 56}{space 1}   -0.96{col 65}{space 3}0.338{col 73}{space 4}-.1328981{col 86}{space 3} .0456739
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}  -.05649{col 45}{space 2} .0433717{col 56}{space 1}   -1.30{col 65}{space 3}0.193{col 73}{space 4}-.1415793{col 86}{space 3} .0285993
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0261622{col 45}{space 2} .0454918{col 56}{space 1}   -0.58{col 65}{space 3}0.565{col 73}{space 4}-.1154108{col 86}{space 3} .0630864
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0005122{col 45}{space 2} .0537471{col 56}{space 1}    0.01{col 65}{space 3}0.992{col 73}{space 4}-.1049322{col 86}{space 3} .1059566
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0473026{col 45}{space 2} .0733867{col 56}{space 1}   -0.64{col 65}{space 3}0.519{col 73}{space 4}-.1912773{col 86}{space 3}  .096672
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1315177{col 45}{space 2} .1126755{col 56}{space 1}    1.17{col 65}{space 3}0.243{col 73}{space 4} -.089536{col 86}{space 3} .3525714
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4159815{col 45}{space 2}  .174879{col 56}{space 1}   -2.38{col 65}{space 3}0.018{col 73}{space 4}-.7590699{col 86}{space 3}-.0728931
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0081279{col 45}{space 2} .2104057{col 56}{space 1}    0.04{col 65}{space 3}0.969{col 73}{space 4}-.4046591{col 86}{space 3} .4209148
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0009559{col 45}{space 2} .0046658{col 56}{space 1}   -0.20{col 65}{space 3}0.838{col 73}{space 4}-.0101096{col 86}{space 3} .0081977
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000132{col 45}{space 2} .0000488{col 56}{space 1}   -0.27{col 65}{space 3}0.786{col 73}{space 4}-.0001089{col 86}{space 3} .0000824
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0413368{col 45}{space 2} .1132638{col 56}{space 1}   -0.36{col 65}{space 3}0.715{col 73}{space 4}-.2635447{col 86}{space 3} .1808712
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1017959{col 45}{space 2} .1142119{col 56}{space 1}   -0.89{col 65}{space 3}0.373{col 73}{space 4}-.3258638{col 86}{space 3}  .122272
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1378373{col 45}{space 2} .1159315{col 56}{space 1}   -1.19{col 65}{space 3}0.235{col 73}{space 4}-.3652788{col 86}{space 3} .0896043
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0446616{col 45}{space 2}  .115084{col 56}{space 1}   -0.39{col 65}{space 3}0.698{col 73}{space 4}-.2704404{col 86}{space 3} .1811173
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0810833{col 45}{space 2} .1166736{col 56}{space 1}   -0.69{col 65}{space 3}0.487{col 73}{space 4}-.3099808{col 86}{space 3} .1478141
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0063537{col 45}{space 2} .0611878{col 56}{space 1}   -0.10{col 65}{space 3}0.917{col 73}{space 4}-.1263958{col 86}{space 3} .1136884
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1335447{col 45}{space 2} .0593809{col 56}{space 1}   -2.25{col 65}{space 3}0.025{col 73}{space 4}-.2500419{col 86}{space 3}-.0170474
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1555797{col 45}{space 2}  .065463{col 56}{space 1}   -2.38{col 65}{space 3}0.018{col 73}{space 4}-.2840091{col 86}{space 3}-.0271503
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2300914{col 45}{space 2} .0609577{col 56}{space 1}   -3.77{col 65}{space 3}0.000{col 73}{space 4} -.349682{col 86}{space 3}-.1105007
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3853508{col 45}{space 2} .0686166{col 56}{space 1}   -5.62{col 65}{space 3}0.000{col 73}{space 4}-.5199672{col 86}{space 3}-.2507344
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2407975{col 45}{space 2} .0648111{col 56}{space 1}   -3.72{col 65}{space 3}0.000{col 73}{space 4}-.3679479{col 86}{space 3}-.1136472
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0212967{col 45}{space 2} .0687659{col 56}{space 1}   -0.31{col 65}{space 3}0.757{col 73}{space 4}-.1562059{col 86}{space 3} .1136125
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2259773{col 45}{space 2} .0731591{col 56}{space 1}   -3.09{col 65}{space 3}0.002{col 73}{space 4}-.3695053{col 86}{space 3}-.0824492
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1791034{col 45}{space 2} .0779851{col 56}{space 1}   -2.30{col 65}{space 3}0.022{col 73}{space 4}-.3320994{col 86}{space 3}-.0261074
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3682757{col 45}{space 2} .0541328{col 56}{space 1}    6.80{col 65}{space 3}0.000{col 73}{space 4} .2620747{col 86}{space 3} .4744768
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0612553{col 45}{space 2} .0683834{col 56}{space 1}   -0.90{col 65}{space 3}0.371{col 73}{space 4} -.195414{col 86}{space 3} .0729035
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0041214{col 45}{space 2} .0707723{col 56}{space 1}   -0.06{col 65}{space 3}0.954{col 73}{space 4} -.142967{col 86}{space 3} .1347241
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0451358{col 45}{space 2} .0715607{col 56}{space 1}    0.63{col 65}{space 3}0.528{col 73}{space 4}-.0952565{col 86}{space 3}  .185528
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4404674{col 45}{space 2} .0482034{col 56}{space 1}   -9.14{col 65}{space 3}0.000{col 73}{space 4}-.5350357{col 86}{space 3} -.345899
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0829751{col 45}{space 2} .0541972{col 56}{space 1}   -1.53{col 65}{space 3}0.126{col 73}{space 4}-.1893025{col 86}{space 3} .0233523
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1505246{col 45}{space 2} .0616222{col 56}{space 1}    2.44{col 65}{space 3}0.015{col 73}{space 4} .0296303{col 86}{space 3} .2714189
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4006105{col 45}{space 2} .0473354{col 56}{space 1}   -8.46{col 65}{space 3}0.000{col 73}{space 4} -.493476{col 86}{space 3}-.3077451
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1331386{col 45}{space 2} .0663465{col 56}{space 1}    2.01{col 65}{space 3}0.045{col 73}{space 4} .0029759{col 86}{space 3} .2633013
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.1959197{col 45}{space 2} .0917769{col 56}{space 1}   -2.13{col 65}{space 3}0.033{col 73}{space 4}-.3759734{col 86}{space 3} -.015866
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1171077{col 45}{space 2} .0882686{col 56}{space 1}   -1.33{col 65}{space 3}0.185{col 73}{space 4}-.2902785{col 86}{space 3} .0560631
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0698894{col 45}{space 2} .1057581{col 56}{space 1}   -0.66{col 65}{space 3}0.509{col 73}{space 4}-.2773722{col 86}{space 3} .1375933
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2242808{col 45}{space 2} .0871566{col 56}{space 1}    2.57{col 65}{space 3}0.010{col 73}{space 4} .0532915{col 86}{space 3}   .39527
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1016178{col 45}{space 2} .1149753{col 56}{space 1}    0.88{col 65}{space 3}0.377{col 73}{space 4} -.123948{col 86}{space 3} .3271835
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9049066{col 45}{space 2} .1532215{col 56}{space 1}    5.91{col 65}{space 3}0.000{col 73}{space 4} .6043072{col 86}{space 3} 1.205506
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,764
                                                {txt}F(1, 1762)        =  {res}    15.50
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0088
                                                {txt}Root MSE          =    {res}  .4944

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1337548{col 26}{space 2} .0339759{col 37}{space 1}    3.94{col 46}{space 3}0.000{col 54}{space 4} .0671175{col 67}{space 3} .2003921
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .420462{col 26}{space 2} .0126895{col 37}{space 1}   33.13{col 46}{space 3}0.000{col 54}{space 4}  .395574{col 67}{space 3} .4453501
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,204
                                                {txt}F(42, 1161)       =  {res}    47.34
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2150
                                                {txt}Root MSE          =    {res}  .4508

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .1143505{col 45}{space 2} .0390139{col 56}{space 1}    2.93{col 65}{space 3}0.003{col 73}{space 4} .0378048{col 86}{space 3} .1908962
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0062372{col 45}{space 2} .0283627{col 56}{space 1}   -0.22{col 65}{space 3}0.826{col 73}{space 4}-.0618852{col 86}{space 3} .0494107
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0317325{col 45}{space 2} .0933114{col 56}{space 1}   -0.34{col 65}{space 3}0.734{col 73}{space 4}-.2148103{col 86}{space 3} .1513452
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0272454{col 45}{space 2} .0579741{col 56}{space 1}   -0.47{col 65}{space 3}0.638{col 73}{space 4}-.1409911{col 86}{space 3} .0865004
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0315145{col 45}{space 2}  .047747{col 56}{space 1}   -0.66{col 65}{space 3}0.509{col 73}{space 4}-.1251946{col 86}{space 3} .0621656
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0553604{col 45}{space 2} .0461976{col 56}{space 1}   -1.20{col 65}{space 3}0.231{col 73}{space 4}-.1460004{col 86}{space 3} .0352797
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0220372{col 45}{space 2} .0490546{col 56}{space 1}   -0.45{col 65}{space 3}0.653{col 73}{space 4}-.1182828{col 86}{space 3} .0742085
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0180015{col 45}{space 2} .0583183{col 56}{space 1}    0.31{col 65}{space 3}0.758{col 73}{space 4}-.0964196{col 86}{space 3} .1324226
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} -.003911{col 45}{space 2} .0846009{col 56}{space 1}   -0.05{col 65}{space 3}0.963{col 73}{space 4}-.1698988{col 86}{space 3} .1620768
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0708107{col 45}{space 2} .1137266{col 56}{space 1}    0.62{col 65}{space 3}0.534{col 73}{space 4}-.1523219{col 86}{space 3} .2939433
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4274972{col 45}{space 2} .1721034{col 56}{space 1}   -2.48{col 65}{space 3}0.013{col 73}{space 4}-.7651656{col 86}{space 3}-.0898287
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .1335382{col 45}{space 2}   .29531{col 56}{space 1}    0.45{col 65}{space 3}0.651{col 73}{space 4}-.4458629{col 86}{space 3} .7129393
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0020579{col 45}{space 2} .0048535{col 56}{space 1}   -0.42{col 65}{space 3}0.672{col 73}{space 4}-.0115806{col 86}{space 3} .0074648
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-6.28e-07{col 45}{space 2} .0000506{col 56}{space 1}   -0.01{col 65}{space 3}0.990{col 73}{space 4}-.0000999{col 86}{space 3} .0000987
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0510914{col 45}{space 2}  .107884{col 56}{space 1}   -0.47{col 65}{space 3}0.636{col 73}{space 4}-.2627609{col 86}{space 3}  .160578
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1234183{col 45}{space 2} .1089431{col 56}{space 1}   -1.13{col 65}{space 3}0.258{col 73}{space 4}-.3371658{col 86}{space 3} .0903291
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.170155{col 45}{space 2}  .111238{col 56}{space 1}   -1.53{col 65}{space 3}0.126{col 73}{space 4} -.388405{col 86}{space 3}  .048095
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0702151{col 45}{space 2} .1101797{col 56}{space 1}   -0.64{col 65}{space 3}0.524{col 73}{space 4}-.2863887{col 86}{space 3} .1459585
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1006937{col 45}{space 2} .1114884{col 56}{space 1}   -0.90{col 65}{space 3}0.367{col 73}{space 4} -.319435{col 86}{space 3} .1180477
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0029752{col 45}{space 2} .0604515{col 56}{space 1}   -0.05{col 65}{space 3}0.961{col 73}{space 4}-.1215815{col 86}{space 3} .1156312
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} -.131564{col 45}{space 2} .0587752{col 56}{space 1}   -2.24{col 65}{space 3}0.025{col 73}{space 4}-.2468815{col 86}{space 3}-.0162466
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1814705{col 45}{space 2} .0672767{col 56}{space 1}   -2.70{col 65}{space 3}0.007{col 73}{space 4}-.3134681{col 86}{space 3} -.049473
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} -.224798{col 45}{space 2} .0619276{col 56}{space 1}   -3.63{col 65}{space 3}0.000{col 73}{space 4}-.3463005{col 86}{space 3}-.1032955
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.385789{col 45}{space 2}  .068312{col 56}{space 1}   -5.65{col 65}{space 3}0.000{col 73}{space 4}-.5198178{col 86}{space 3}-.2517603
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3060877{col 45}{space 2} .0658834{col 56}{space 1}   -4.65{col 65}{space 3}0.000{col 73}{space 4}-.4353515{col 86}{space 3}-.1768238
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} -.020867{col 45}{space 2} .0691635{col 56}{space 1}   -0.30{col 65}{space 3}0.763{col 73}{space 4}-.1565665{col 86}{space 3} .1148324
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2290475{col 45}{space 2} .0730716{col 56}{space 1}   -3.13{col 65}{space 3}0.002{col 73}{space 4}-.3724147{col 86}{space 3}-.0856804
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1847941{col 45}{space 2} .0777167{col 56}{space 1}   -2.38{col 65}{space 3}0.018{col 73}{space 4}-.3372751{col 86}{space 3}-.0323131
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3675846{col 45}{space 2} .0541176{col 56}{space 1}    6.79{col 65}{space 3}0.000{col 73}{space 4} .2614052{col 86}{space 3} .4737639
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0650681{col 45}{space 2}  .068602{col 56}{space 1}   -0.95{col 65}{space 3}0.343{col 73}{space 4}-.1996658{col 86}{space 3} .0695296
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0007925{col 45}{space 2} .0710299{col 56}{space 1}    0.01{col 65}{space 3}0.991{col 73}{space 4}-.1385688{col 86}{space 3} .1401539
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0416436{col 45}{space 2} .0716158{col 56}{space 1}    0.58{col 65}{space 3}0.561{col 73}{space 4}-.0988673{col 86}{space 3} .1821544
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4281247{col 45}{space 2} .0520397{col 56}{space 1}   -8.23{col 65}{space 3}0.000{col 73}{space 4}-.5302271{col 86}{space 3}-.3260222
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0820522{col 45}{space 2} .0544731{col 56}{space 1}   -1.51{col 65}{space 3}0.132{col 73}{space 4}-.1889289{col 86}{space 3} .0248244
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1534532{col 45}{space 2}  .061079{col 56}{space 1}    2.51{col 65}{space 3}0.012{col 73}{space 4} .0336157{col 86}{space 3} .2732908
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0297205{col 45}{space 2} .0728947{col 56}{space 1}   -0.41{col 65}{space 3}0.684{col 73}{space 4}-.1727407{col 86}{space 3} .1132996
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}  .130079{col 45}{space 2} .0663958{col 56}{space 1}    1.96{col 65}{space 3}0.050{col 73}{space 4}-.0001902{col 86}{space 3} .2603483
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2004497{col 45}{space 2} .0916752{col 56}{space 1}   -2.19{col 65}{space 3}0.029{col 73}{space 4}-.3803174{col 86}{space 3} -.020582
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1235401{col 45}{space 2} .0893363{col 56}{space 1}   -1.38{col 65}{space 3}0.167{col 73}{space 4}-.2988187{col 86}{space 3} .0517386
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0685249{col 45}{space 2} .1061136{col 56}{space 1}   -0.65{col 65}{space 3}0.519{col 73}{space 4}-.2767207{col 86}{space 3} .1396709
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2501716{col 45}{space 2} .0890881{col 56}{space 1}    2.81{col 65}{space 3}0.005{col 73}{space 4} .0753798{col 86}{space 3} .4249633
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1296798{col 45}{space 2} .1173857{col 56}{space 1}    1.10{col 65}{space 3}0.270{col 73}{space 4}-.1006321{col 86}{space 3} .3599917
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9439456{col 45}{space 2} .1518845{col 56}{space 1}    6.21{col 65}{space 3}0.000{col 73}{space 4} .6459467{col 86}{space 3} 1.241945
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,620
                                                {txt}F(1, 1618)        =  {res}    21.86
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0127
                                                {txt}Root MSE          =    {res} .49694

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}  .166403{col 26}{space 2} .0355907{col 37}{space 1}    4.68{col 46}{space 3}0.000{col 54}{space 4} .0965942{col 67}{space 3} .2362118
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4644381{col 26}{space 2}  .013309{col 37}{space 1}   34.90{col 46}{space 3}0.000{col 54}{space 4} .4383335{col 67}{space 3} .4905427
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,289
                                                {txt}F(42, 1246)       =  {res}    19.88
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2541
                                                {txt}Root MSE          =    {res} .43832

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0944981{col 45}{space 2} .0360398{col 56}{space 1}    2.62{col 65}{space 3}0.009{col 73}{space 4} .0237927{col 86}{space 3} .1652035
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0231089{col 45}{space 2} .0266175{col 56}{space 1}   -0.87{col 65}{space 3}0.385{col 73}{space 4} -.075329{col 86}{space 3} .0291111
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0208245{col 45}{space 2} .0905116{col 56}{space 1}    0.23{col 65}{space 3}0.818{col 73}{space 4}-.1567474{col 86}{space 3} .1983965
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0026999{col 45}{space 2} .0581339{col 56}{space 1}   -0.05{col 65}{space 3}0.963{col 73}{space 4}-.1167511{col 86}{space 3} .1113513
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0189589{col 45}{space 2} .0459357{col 56}{space 1}   -0.41{col 65}{space 3}0.680{col 73}{space 4}-.1090788{col 86}{space 3}  .071161
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0400313{col 45}{space 2}  .043465{col 56}{space 1}   -0.92{col 65}{space 3}0.357{col 73}{space 4} -.125304{col 86}{space 3} .0452415
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0161868{col 45}{space 2} .0461135{col 56}{space 1}   -0.35{col 65}{space 3}0.726{col 73}{space 4}-.1066556{col 86}{space 3} .0742819
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0062983{col 45}{space 2} .0543288{col 56}{space 1}    0.12{col 65}{space 3}0.908{col 73}{space 4}-.1002878{col 86}{space 3} .1128844
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0393217{col 45}{space 2} .0737034{col 56}{space 1}   -0.53{col 65}{space 3}0.594{col 73}{space 4}-.1839182{col 86}{space 3} .1052749
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1894936{col 45}{space 2} .1143065{col 56}{space 1}    1.66{col 65}{space 3}0.098{col 73}{space 4}-.0347608{col 86}{space 3} .4137481
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4216783{col 45}{space 2} .1872585{col 56}{space 1}   -2.25{col 65}{space 3}0.025{col 73}{space 4}-.7890551{col 86}{space 3}-.0543015
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0755676{col 45}{space 2} .2210598{col 56}{space 1}   -0.34{col 65}{space 3}0.733{col 73}{space 4}-.5092581{col 86}{space 3} .3581229
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0017414{col 45}{space 2} .0046224{col 56}{space 1}   -0.38{col 65}{space 3}0.706{col 73}{space 4}-.0108098{col 86}{space 3} .0073271
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-5.30e-06{col 45}{space 2}  .000048{col 56}{space 1}   -0.11{col 65}{space 3}0.912{col 73}{space 4}-.0000995{col 86}{space 3}  .000089
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0444999{col 45}{space 2} .1092061{col 56}{space 1}   -0.41{col 65}{space 3}0.684{col 73}{space 4}-.2587481{col 86}{space 3} .1697482
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1204493{col 45}{space 2} .1098927{col 56}{space 1}   -1.10{col 65}{space 3}0.273{col 73}{space 4}-.3360444{col 86}{space 3} .0951459
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1458212{col 45}{space 2} .1114325{col 56}{space 1}   -1.31{col 65}{space 3}0.191{col 73}{space 4}-.3644372{col 86}{space 3} .0727949
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0577872{col 45}{space 2} .1108317{col 56}{space 1}   -0.52{col 65}{space 3}0.602{col 73}{space 4}-.2752245{col 86}{space 3} .1596501
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0816732{col 45}{space 2}  .112107{col 56}{space 1}   -0.73{col 65}{space 3}0.466{col 73}{space 4}-.3016125{col 86}{space 3} .1382661
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0013516{col 45}{space 2} .0600179{col 56}{space 1}    0.02{col 65}{space 3}0.982{col 73}{space 4}-.1163957{col 86}{space 3}  .119099
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1329249{col 45}{space 2} .0584239{col 56}{space 1}   -2.28{col 65}{space 3}0.023{col 73}{space 4}-.2475451{col 86}{space 3}-.0183048
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1776942{col 45}{space 2} .0646652{col 56}{space 1}   -2.75{col 65}{space 3}0.006{col 73}{space 4} -.304559{col 86}{space 3}-.0508295
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2072365{col 45}{space 2} .0599984{col 56}{space 1}   -3.45{col 65}{space 3}0.001{col 73}{space 4}-.3249455{col 86}{space 3}-.0895275
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4154163{col 45}{space 2}  .069523{col 56}{space 1}   -5.98{col 65}{space 3}0.000{col 73}{space 4}-.5518114{col 86}{space 3}-.2790211
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2385748{col 45}{space 2} .0637185{col 56}{space 1}   -3.74{col 65}{space 3}0.000{col 73}{space 4}-.3635823{col 86}{space 3}-.1135674
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0160403{col 45}{space 2} .0689922{col 56}{space 1}   -0.23{col 65}{space 3}0.816{col 73}{space 4}-.1513941{col 86}{space 3} .1193134
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2399418{col 45}{space 2} .0723653{col 56}{space 1}   -3.32{col 65}{space 3}0.001{col 73}{space 4}-.3819132{col 86}{space 3}-.0979705
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1724229{col 45}{space 2} .0785095{col 56}{space 1}   -2.20{col 65}{space 3}0.028{col 73}{space 4}-.3264482{col 86}{space 3}-.0183976
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3553007{col 45}{space 2} .0544171{col 56}{space 1}    6.53{col 65}{space 3}0.000{col 73}{space 4} .2485414{col 86}{space 3}   .46206
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0693913{col 45}{space 2} .0690646{col 56}{space 1}   -1.00{col 65}{space 3}0.315{col 73}{space 4}-.2048871{col 86}{space 3} .0661046
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}-.0055144{col 45}{space 2} .0711803{col 56}{space 1}   -0.08{col 65}{space 3}0.938{col 73}{space 4}-.1451609{col 86}{space 3} .1341322
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0335012{col 45}{space 2}  .071451{col 56}{space 1}    0.47{col 65}{space 3}0.639{col 73}{space 4}-.1066763{col 86}{space 3} .1736788
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4512942{col 45}{space 2} .0481623{col 56}{space 1}   -9.37{col 65}{space 3}0.000{col 73}{space 4}-.5457824{col 86}{space 3} -.356806
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0801639{col 45}{space 2} .0543436{col 56}{space 1}   -1.48{col 65}{space 3}0.140{col 73}{space 4}-.1867791{col 86}{space 3} .0264512
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1443287{col 45}{space 2} .0609851{col 56}{space 1}    2.37{col 65}{space 3}0.018{col 73}{space 4} .0246839{col 86}{space 3} .2639734
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0376488{col 45}{space 2}  .072302{col 56}{space 1}   -0.52{col 65}{space 3}0.603{col 73}{space 4}-.1794959{col 86}{space 3} .1041984
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4075365{col 45}{space 2} .0473701{col 56}{space 1}   -8.60{col 65}{space 3}0.000{col 73}{space 4}-.5004705{col 86}{space 3}-.3146025
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2136019{col 45}{space 2} .0910912{col 56}{space 1}   -2.34{col 65}{space 3}0.019{col 73}{space 4}-.3923109{col 86}{space 3}-.0348929
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1332203{col 45}{space 2} .0895993{col 56}{space 1}   -1.49{col 65}{space 3}0.137{col 73}{space 4}-.3090025{col 86}{space 3} .0425618
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0874831{col 45}{space 2} .1068839{col 56}{space 1}   -0.82{col 65}{space 3}0.413{col 73}{space 4}-.2971753{col 86}{space 3} .1222091
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2512361{col 45}{space 2} .0878727{col 56}{space 1}    2.86{col 65}{space 3}0.004{col 73}{space 4} .0788414{col 86}{space 3} .4236308
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1224279{col 45}{space 2} .1152283{col 56}{space 1}    1.06{col 65}{space 3}0.288{col 73}{space 4}-.1036351{col 86}{space 3} .3484908
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9314817{col 45}{space 2} .1502767{col 56}{space 1}    6.20{col 65}{space 3}0.000{col 73}{space 4} .6366583{col 86}{space 3} 1.226305
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,773
                                                {txt}F(1, 1771)        =  {res}     9.96
                                                {txt}Prob > F          = {res}    0.0016
                                                {txt}R-squared         = {res}    0.0057
                                                {txt}Root MSE          =    {res} .49438

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1083369{col 26}{space 2} .0343234{col 37}{space 1}    3.16{col 46}{space 3}0.002{col 54}{space 4} .0410182{col 67}{space 3} .1756556
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4181937{col 26}{space 2} .0126259{col 37}{space 1}   33.12{col 46}{space 3}0.000{col 54}{space 4} .3934305{col 67}{space 3} .4429569
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,321
                                                {txt}F(42, 1278)       =  {res}    20.25
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2549
                                                {txt}Root MSE          =    {res} .43837

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0986576{col 45}{space 2} .0348963{col 56}{space 1}    2.83{col 65}{space 3}0.005{col 73}{space 4} .0301973{col 86}{space 3} .1671179
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0158829{col 45}{space 2} .0261366{col 56}{space 1}   -0.61{col 65}{space 3}0.544{col 73}{space 4}-.0671582{col 86}{space 3} .0353925
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0115516{col 45}{space 2} .0900129{col 56}{space 1}   -0.13{col 65}{space 3}0.898{col 73}{space 4}-.1881409{col 86}{space 3} .1650377
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0059069{col 45}{space 2} .0570327{col 56}{space 1}    0.10{col 65}{space 3}0.918{col 73}{space 4}-.1059811{col 86}{space 3} .1177949
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0430475{col 45}{space 2} .0449298{col 56}{space 1}   -0.96{col 65}{space 3}0.338{col 73}{space 4}-.1311917{col 86}{space 3} .0450967
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0541867{col 45}{space 2} .0427616{col 56}{space 1}   -1.27{col 65}{space 3}0.205{col 73}{space 4}-.1380773{col 86}{space 3} .0297039
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0366451{col 45}{space 2} .0451515{col 56}{space 1}   -0.81{col 65}{space 3}0.417{col 73}{space 4}-.1252243{col 86}{space 3} .0519341
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0151117{col 45}{space 2} .0535924{col 56}{space 1}   -0.28{col 65}{space 3}0.778{col 73}{space 4}-.1202504{col 86}{space 3}  .090027
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0612316{col 45}{space 2} .0734903{col 56}{space 1}   -0.83{col 65}{space 3}0.405{col 73}{space 4}-.2054064{col 86}{space 3} .0829433
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0972887{col 45}{space 2} .1142946{col 56}{space 1}    0.85{col 65}{space 3}0.395{col 73}{space 4} -.126937{col 86}{space 3} .3215143
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.430141{col 45}{space 2}  .181321{col 56}{space 1}   -2.37{col 65}{space 3}0.018{col 73}{space 4}-.7858605{col 86}{space 3}-.0744214
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0136334{col 45}{space 2} .2104343{col 56}{space 1}    0.06{col 65}{space 3}0.948{col 73}{space 4}-.3992013{col 86}{space 3} .4264681
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0004567{col 45}{space 2} .0045451{col 56}{space 1}    0.10{col 65}{space 3}0.920{col 73}{space 4}  -.00846{col 86}{space 3} .0093734
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000281{col 45}{space 2} .0000472{col 56}{space 1}   -0.59{col 65}{space 3}0.552{col 73}{space 4}-.0001208{col 86}{space 3} .0000646
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0946141{col 45}{space 2} .1078669{col 56}{space 1}   -0.88{col 65}{space 3}0.381{col 73}{space 4}-.3062297{col 86}{space 3} .1170015
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1621822{col 45}{space 2}   .10904{col 56}{space 1}   -1.49{col 65}{space 3}0.137{col 73}{space 4}-.3760994{col 86}{space 3} .0517349
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1826506{col 45}{space 2} .1106522{col 56}{space 1}   -1.65{col 65}{space 3}0.099{col 73}{space 4}-.3997305{col 86}{space 3} .0344293
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1061704{col 45}{space 2} .1098818{col 56}{space 1}   -0.97{col 65}{space 3}0.334{col 73}{space 4}-.3217391{col 86}{space 3} .1093982
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1278145{col 45}{space 2} .1113403{col 56}{space 1}   -1.15{col 65}{space 3}0.251{col 73}{space 4}-.3462444{col 86}{space 3} .0906155
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  -.02351{col 45}{space 2} .0608868{col 56}{space 1}   -0.39{col 65}{space 3}0.699{col 73}{space 4} -.142959{col 86}{space 3} .0959391
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1618286{col 45}{space 2} .0593067{col 56}{space 1}   -2.73{col 65}{space 3}0.006{col 73}{space 4}-.2781779{col 86}{space 3}-.0454793
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.2024225{col 45}{space 2} .0653893{col 56}{space 1}   -3.10{col 65}{space 3}0.002{col 73}{space 4}-.3307047{col 86}{space 3}-.0741403
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2397205{col 45}{space 2} .0610903{col 56}{space 1}   -3.92{col 65}{space 3}0.000{col 73}{space 4}-.3595688{col 86}{space 3}-.1198721
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4081399{col 45}{space 2} .0685879{col 56}{space 1}   -5.95{col 65}{space 3}0.000{col 73}{space 4}-.5426972{col 86}{space 3}-.2735826
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2613731{col 45}{space 2} .0648648{col 56}{space 1}   -4.03{col 65}{space 3}0.000{col 73}{space 4}-.3886262{col 86}{space 3}-.1341199
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0236041{col 45}{space 2} .0689954{col 56}{space 1}   -0.34{col 65}{space 3}0.732{col 73}{space 4}-.1589608{col 86}{space 3} .1117525
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2293389{col 45}{space 2} .0721638{col 56}{space 1}   -3.18{col 65}{space 3}0.002{col 73}{space 4}-.3709114{col 86}{space 3}-.0877665
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1798828{col 45}{space 2} .0778829{col 56}{space 1}   -2.31{col 65}{space 3}0.021{col 73}{space 4}-.3326752{col 86}{space 3}-.0270904
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3646033{col 45}{space 2} .0544238{col 56}{space 1}    6.70{col 65}{space 3}0.000{col 73}{space 4} .2578336{col 86}{space 3} .4713731
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0634739{col 45}{space 2} .0686675{col 56}{space 1}   -0.92{col 65}{space 3}0.355{col 73}{space 4}-.1981872{col 86}{space 3} .0712394
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0031682{col 45}{space 2}  .070696{col 56}{space 1}    0.04{col 65}{space 3}0.964{col 73}{space 4}-.1355249{col 86}{space 3} .1418612
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0416975{col 45}{space 2} .0713083{col 56}{space 1}    0.58{col 65}{space 3}0.559{col 73}{space 4}-.0981968{col 86}{space 3} .1815917
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} -.442877{col 45}{space 2} .0481313{col 56}{space 1}   -9.20{col 65}{space 3}0.000{col 73}{space 4} -.537302{col 86}{space 3}-.3484519
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0811887{col 45}{space 2} .0544232{col 56}{space 1}   -1.49{col 65}{space 3}0.136{col 73}{space 4}-.1879573{col 86}{space 3} .0255798
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1453864{col 45}{space 2} .0614536{col 56}{space 1}    2.37{col 65}{space 3}0.018{col 73}{space 4} .0248253{col 86}{space 3} .2659475
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0332402{col 45}{space 2}  .072475{col 56}{space 1}   -0.46{col 65}{space 3}0.647{col 73}{space 4}-.1754233{col 86}{space 3} .1089429
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3990648{col 45}{space 2} .0471959{col 56}{space 1}   -8.46{col 65}{space 3}0.000{col 73}{space 4}-.4916547{col 86}{space 3}-.3064749
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1360563{col 45}{space 2}  .066313{col 56}{space 1}    2.05{col 65}{space 3}0.040{col 73}{space 4}  .005962{col 86}{space 3} .2661505
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1206448{col 45}{space 2} .0891861{col 56}{space 1}   -1.35{col 65}{space 3}0.176{col 73}{space 4}-.2956121{col 86}{space 3} .0543225
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} -.076961{col 45}{space 2}  .106693{col 56}{space 1}   -0.72{col 65}{space 3}0.471{col 73}{space 4}-.2862736{col 86}{space 3} .1323516
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2529534{col 45}{space 2}  .086849{col 56}{space 1}    2.91{col 65}{space 3}0.004{col 73}{space 4}  .082571{col 86}{space 3} .4233357
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1268498{col 45}{space 2} .1148849{col 56}{space 1}    1.10{col 65}{space 3}0.270{col 73}{space 4}-.0985339{col 86}{space 3} .3522335
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9580181{col 45}{space 2} .1478322{col 56}{space 1}    6.48{col 65}{space 3}0.000{col 73}{space 4} .6679977{col 86}{space 3} 1.248039
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,806
                                                {txt}F(1, 1804)        =  {res}    12.17
                                                {txt}Prob > F          = {res}    0.0005
                                                {txt}R-squared         = {res}    0.0068
                                                {txt}Root MSE          =    {res} .49526

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1171623{col 26}{space 2} .0335908{col 37}{space 1}    3.49{col 46}{space 3}0.000{col 54}{space 4} .0512814{col 67}{space 3} .1830432
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4258065{col 26}{space 2} .0125664{col 37}{space 1}   33.88{col 46}{space 3}0.000{col 54}{space 4} .4011603{col 67}{space 3} .4504526
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,317
                                                {txt}F(42, 1274)       =  {res}    20.85
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2568
                                                {txt}Root MSE          =    {res} .43781

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0959962{col 45}{space 2} .0348586{col 56}{space 1}    2.75{col 65}{space 3}0.006{col 73}{space 4} .0276096{col 86}{space 3} .1643828
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0287005{col 45}{space 2} .0262781{col 56}{space 1}   -1.09{col 65}{space 3}0.275{col 73}{space 4}-.0802536{col 86}{space 3} .0228525
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0079864{col 45}{space 2} .0897144{col 56}{space 1}   -0.09{col 65}{space 3}0.929{col 73}{space 4}-.1839907{col 86}{space 3} .1680179
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0225686{col 45}{space 2} .0571279{col 56}{space 1}   -0.40{col 65}{space 3}0.693{col 73}{space 4}-.1346437{col 86}{space 3} .0895065
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0280744{col 45}{space 2} .0451811{col 56}{space 1}   -0.62{col 65}{space 3}0.534{col 73}{space 4} -.116712{col 86}{space 3} .0605632
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} -.053097{col 45}{space 2} .0427374{col 56}{space 1}   -1.24{col 65}{space 3}0.214{col 73}{space 4}-.1369404{col 86}{space 3} .0307463
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0388065{col 45}{space 2} .0453968{col 56}{space 1}   -0.85{col 65}{space 3}0.393{col 73}{space 4}-.1278673{col 86}{space 3} .0502542
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.011665{col 45}{space 2} .0537433{col 56}{space 1}   -0.22{col 65}{space 3}0.828{col 73}{space 4}-.1171001{col 86}{space 3} .0937701
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0624015{col 45}{space 2} .0733493{col 56}{space 1}   -0.85{col 65}{space 3}0.395{col 73}{space 4}-.2063002{col 86}{space 3} .0814971
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1292255{col 45}{space 2}  .110233{col 56}{space 1}    1.17{col 65}{space 3}0.241{col 73}{space 4}-.0870328{col 86}{space 3} .3454837
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4451435{col 45}{space 2} .1862218{col 56}{space 1}   -2.39{col 65}{space 3}0.017{col 73}{space 4}-.8104787{col 86}{space 3}-.0798084
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0097532{col 45}{space 2} .2136695{col 56}{space 1}    0.05{col 65}{space 3}0.964{col 73}{space 4}-.4094294{col 86}{space 3} .4289359
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} -.001311{col 45}{space 2} .0046706{col 56}{space 1}   -0.28{col 65}{space 3}0.779{col 73}{space 4}-.0104738{col 86}{space 3} .0078519
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-8.79e-06{col 45}{space 2} .0000489{col 56}{space 1}   -0.18{col 65}{space 3}0.857{col 73}{space 4}-.0001046{col 86}{space 3} .0000871
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} -.051692{col 45}{space 2} .1055952{col 56}{space 1}   -0.49{col 65}{space 3}0.625{col 73}{space 4}-.2588515{col 86}{space 3} .1554676
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1247637{col 45}{space 2} .1072789{col 56}{space 1}   -1.16{col 65}{space 3}0.245{col 73}{space 4}-.3352265{col 86}{space 3} .0856991
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1582169{col 45}{space 2} .1086115{col 56}{space 1}   -1.46{col 65}{space 3}0.145{col 73}{space 4} -.371294{col 86}{space 3} .0548601
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0927235{col 45}{space 2} .1078426{col 56}{space 1}   -0.86{col 65}{space 3}0.390{col 73}{space 4}-.3042921{col 86}{space 3} .1188451
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0772962{col 45}{space 2} .1093676{col 56}{space 1}   -0.71{col 65}{space 3}0.480{col 73}{space 4}-.2918567{col 86}{space 3} .1372642
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0066438{col 45}{space 2} .0596079{col 56}{space 1}   -0.11{col 65}{space 3}0.911{col 73}{space 4}-.1235841{col 86}{space 3} .1102966
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1554259{col 45}{space 2} .0581498{col 56}{space 1}   -2.67{col 65}{space 3}0.008{col 73}{space 4}-.2695058{col 86}{space 3}-.0413461
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.2003288{col 45}{space 2} .0643276{col 56}{space 1}   -3.11{col 65}{space 3}0.002{col 73}{space 4}-.3265285{col 86}{space 3} -.074129
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2287537{col 45}{space 2}  .060057{col 56}{space 1}   -3.81{col 65}{space 3}0.000{col 73}{space 4}-.3465752{col 86}{space 3}-.1109321
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4040273{col 45}{space 2} .0677338{col 56}{space 1}   -5.96{col 65}{space 3}0.000{col 73}{space 4}-.5369094{col 86}{space 3}-.2711453
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2570851{col 45}{space 2} .0636612{col 56}{space 1}   -4.04{col 65}{space 3}0.000{col 73}{space 4}-.3819773{col 86}{space 3}-.1321928
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0231569{col 45}{space 2}  .069233{col 56}{space 1}   -0.33{col 65}{space 3}0.738{col 73}{space 4}  -.15898{col 86}{space 3} .1126663
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2299921{col 45}{space 2} .0721039{col 56}{space 1}   -3.19{col 65}{space 3}0.001{col 73}{space 4}-.3714476{col 86}{space 3}-.0885367
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}  -.18005{col 45}{space 2}  .077356{col 56}{space 1}   -2.33{col 65}{space 3}0.020{col 73}{space 4}-.3318092{col 86}{space 3}-.0282908
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3678045{col 45}{space 2} .0537098{col 56}{space 1}    6.85{col 65}{space 3}0.000{col 73}{space 4} .2624351{col 86}{space 3} .4731738
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0654471{col 45}{space 2} .0689664{col 56}{space 1}   -0.95{col 65}{space 3}0.343{col 73}{space 4}-.2007474{col 86}{space 3} .0698531
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0043116{col 45}{space 2} .0709135{col 56}{space 1}    0.06{col 65}{space 3}0.952{col 73}{space 4}-.1348086{col 86}{space 3} .1434317
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0381444{col 45}{space 2} .0711094{col 56}{space 1}    0.54{col 65}{space 3}0.592{col 73}{space 4}  -.10136{col 86}{space 3} .1776487
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4412465{col 45}{space 2} .0482021{col 56}{space 1}   -9.15{col 65}{space 3}0.000{col 73}{space 4}-.5358107{col 86}{space 3}-.3466822
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0791945{col 45}{space 2} .0543528{col 56}{space 1}   -1.46{col 65}{space 3}0.145{col 73}{space 4}-.1858254{col 86}{space 3} .0274364
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1431602{col 45}{space 2} .0612026{col 56}{space 1}    2.34{col 65}{space 3}0.019{col 73}{space 4} .0230913{col 86}{space 3} .2632291
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0324352{col 45}{space 2} .0718252{col 56}{space 1}   -0.45{col 65}{space 3}0.652{col 73}{space 4}-.1733439{col 86}{space 3} .1084735
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4011792{col 45}{space 2} .0474511{col 56}{space 1}   -8.45{col 65}{space 3}0.000{col 73}{space 4}-.4942702{col 86}{space 3}-.3080882
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1354226{col 45}{space 2} .0665493{col 56}{space 1}    2.03{col 65}{space 3}0.042{col 73}{space 4} .0048642{col 86}{space 3} .2659809
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2110243{col 45}{space 2} .0912659{col 56}{space 1}   -2.31{col 65}{space 3}0.021{col 73}{space 4}-.3900722{col 86}{space 3}-.0319763
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0776673{col 45}{space 2} .1078026{col 56}{space 1}   -0.72{col 65}{space 3}0.471{col 73}{space 4}-.2891575{col 86}{space 3} .1338229
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2614176{col 45}{space 2} .0873217{col 56}{space 1}    2.99{col 65}{space 3}0.003{col 73}{space 4} .0901075{col 86}{space 3} .4327277
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1325523{col 45}{space 2} .1145362{col 56}{space 1}    1.16{col 65}{space 3}0.247{col 73}{space 4} -.092148{col 86}{space 3} .3572527
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9588487{col 45}{space 2} .1467441{col 56}{space 1}    6.53{col 65}{space 3}0.000{col 73}{space 4}  .670962{col 86}{space 3} 1.246735
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,789
                                                {txt}F(1, 1787)        =  {res}    11.18
                                                {txt}Prob > F          = {res}    0.0008
                                                {txt}R-squared         = {res}    0.0063
                                                {txt}Root MSE          =    {res} .49542

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2}  .112448{col 26}{space 2} .0336368{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4} .0464765{col 67}{space 3} .1784196
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4266145{col 26}{space 2}  .012639{col 37}{space 1}   33.75{col 46}{space 3}0.000{col 54}{space 4} .4018257{col 67}{space 3} .4514033
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,331
                                                {txt}F(42, 1288)       =  {res}    20.76
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2531
                                                {txt}Root MSE          =    {res} .43879

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0947727{col 45}{space 2} .0352706{col 56}{space 1}    2.69{col 65}{space 3}0.007{col 73}{space 4} .0255787{col 86}{space 3} .1639668
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0142083{col 45}{space 2}  .026048{col 56}{space 1}   -0.55{col 65}{space 3}0.586{col 73}{space 4}-.0653095{col 86}{space 3} .0368928
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0095435{col 45}{space 2} .0900186{col 56}{space 1}   -0.11{col 65}{space 3}0.916{col 73}{space 4}-.1861426{col 86}{space 3} .1670556
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}-.0185977{col 45}{space 2} .0569699{col 56}{space 1}   -0.33{col 65}{space 3}0.744{col 73}{space 4}-.1303616{col 86}{space 3} .0931662
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0416781{col 45}{space 2} .0449357{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.1298333{col 86}{space 3} .0464771
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0526136{col 45}{space 2} .0426954{col 56}{space 1}   -1.23{col 65}{space 3}0.218{col 73}{space 4}-.1363738{col 86}{space 3} .0311466
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0387881{col 45}{space 2} .0451288{col 56}{space 1}   -0.86{col 65}{space 3}0.390{col 73}{space 4}-.1273222{col 86}{space 3}  .049746
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.010296{col 45}{space 2} .0538588{col 56}{space 1}   -0.19{col 65}{space 3}0.848{col 73}{space 4}-.1159567{col 86}{space 3} .0953646
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0550464{col 45}{space 2} .0735529{col 56}{space 1}   -0.75{col 65}{space 3}0.454{col 73}{space 4}-.1993431{col 86}{space 3} .0892503
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1608926{col 45}{space 2} .1116987{col 56}{space 1}    1.44{col 65}{space 3}0.150{col 73}{space 4}-.0582387{col 86}{space 3}  .380024
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4441912{col 45}{space 2} .1808787{col 56}{space 1}   -2.46{col 65}{space 3}0.014{col 73}{space 4}-.7990404{col 86}{space 3} -.089342
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0118923{col 45}{space 2} .2114558{col 56}{space 1}    0.06{col 65}{space 3}0.955{col 73}{space 4}-.4029433{col 86}{space 3}  .426728
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0001842{col 45}{space 2} .0045452{col 56}{space 1}   -0.04{col 65}{space 3}0.968{col 73}{space 4} -.009101{col 86}{space 3} .0087326
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-.0000214{col 45}{space 2} .0000473{col 56}{space 1}   -0.45{col 65}{space 3}0.651{col 73}{space 4}-.0001142{col 86}{space 3} .0000715
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0592685{col 45}{space 2}  .105671{col 56}{space 1}   -0.56{col 65}{space 3}0.575{col 73}{space 4}-.2665746{col 86}{space 3} .1480377
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1412682{col 45}{space 2} .1068403{col 56}{space 1}   -1.32{col 65}{space 3}0.186{col 73}{space 4}-.3508684{col 86}{space 3}  .068332
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.167422{col 45}{space 2} .1084241{col 56}{space 1}   -1.54{col 65}{space 3}0.123{col 73}{space 4}-.3801291{col 86}{space 3} .0452852
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0872182{col 45}{space 2} .1076047{col 56}{space 1}   -0.81{col 65}{space 3}0.418{col 73}{space 4}-.2983179{col 86}{space 3} .1238814
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0928108{col 45}{space 2} .1090725{col 56}{space 1}   -0.85{col 65}{space 3}0.395{col 73}{space 4}  -.30679{col 86}{space 3} .1211684
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}-.0158506{col 45}{space 2} .0596427{col 56}{space 1}   -0.27{col 65}{space 3}0.790{col 73}{space 4}-.1328581{col 86}{space 3}  .101157
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1497197{col 45}{space 2} .0579733{col 56}{space 1}   -2.58{col 65}{space 3}0.010{col 73}{space 4}-.2634522{col 86}{space 3}-.0359871
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1947243{col 45}{space 2} .0642316{col 56}{space 1}   -3.03{col 65}{space 3}0.002{col 73}{space 4}-.3207344{col 86}{space 3}-.0687141
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2289678{col 45}{space 2} .0598488{col 56}{space 1}   -3.83{col 65}{space 3}0.000{col 73}{space 4}-.3463796{col 86}{space 3} -.111556
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.4016342{col 45}{space 2} .0675508{col 56}{space 1}   -5.95{col 65}{space 3}0.000{col 73}{space 4}-.5341558{col 86}{space 3}-.2691126
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2555092{col 45}{space 2} .0634661{col 56}{space 1}   -4.03{col 65}{space 3}0.000{col 73}{space 4}-.3800175{col 86}{space 3}-.1310009
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0243669{col 45}{space 2} .0691085{col 56}{space 1}   -0.35{col 65}{space 3}0.724{col 73}{space 4}-.1599444{col 86}{space 3} .1112107
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2303058{col 45}{space 2} .0722927{col 56}{space 1}   -3.19{col 65}{space 3}0.001{col 73}{space 4}-.3721303{col 86}{space 3}-.0884814
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1828629{col 45}{space 2} .0777699{col 56}{space 1}   -2.35{col 65}{space 3}0.019{col 73}{space 4}-.3354326{col 86}{space 3}-.0302933
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3627683{col 45}{space 2} .0538959{col 56}{space 1}    6.73{col 65}{space 3}0.000{col 73}{space 4}  .257035{col 86}{space 3} .4685016
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0647123{col 45}{space 2} .0688672{col 56}{space 1}   -0.94{col 65}{space 3}0.348{col 73}{space 4}-.1998165{col 86}{space 3} .0703919
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0021202{col 45}{space 2} .0709962{col 56}{space 1}    0.03{col 65}{space 3}0.976{col 73}{space 4}-.1371608{col 86}{space 3} .1414012
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}  .039644{col 45}{space 2} .0710084{col 56}{space 1}    0.56{col 65}{space 3}0.577{col 73}{space 4}-.0996609{col 86}{space 3} .1789489
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4435552{col 45}{space 2}  .048089{col 56}{space 1}   -9.22{col 65}{space 3}0.000{col 73}{space 4}-.5378966{col 86}{space 3}-.3492138
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0800557{col 45}{space 2} .0543884{col 56}{space 1}   -1.47{col 65}{space 3}0.141{col 73}{space 4}-.1867552{col 86}{space 3} .0266439
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1467215{col 45}{space 2} .0610966{col 56}{space 1}    2.40{col 65}{space 3}0.016{col 73}{space 4} .0268617{col 86}{space 3} .2665812
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}  -.03288{col 45}{space 2} .0720777{col 56}{space 1}   -0.46{col 65}{space 3}0.648{col 73}{space 4}-.1742825{col 86}{space 3} .1085226
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4017347{col 45}{space 2} .0472548{col 56}{space 1}   -8.50{col 65}{space 3}0.000{col 73}{space 4}-.4944394{col 86}{space 3}-.3090299
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1326561{col 45}{space 2} .0664821{col 56}{space 1}    2.00{col 65}{space 3}0.046{col 73}{space 4} .0022309{col 86}{space 3} .2630812
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2089728{col 45}{space 2}  .091488{col 56}{space 1}   -2.28{col 65}{space 3}0.023{col 73}{space 4}-.3884546{col 86}{space 3} -.029491
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1240435{col 45}{space 2} .0898583{col 56}{space 1}   -1.38{col 65}{space 3}0.168{col 73}{space 4}-.3003281{col 86}{space 3} .0522412
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2569111{col 45}{space 2} .0869376{col 56}{space 1}    2.96{col 65}{space 3}0.003{col 73}{space 4} .0863563{col 86}{space 3} .4274659
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1285734{col 45}{space 2} .1150372{col 56}{space 1}    1.12{col 65}{space 3}0.264{col 73}{space 4}-.0971073{col 86}{space 3} .3542542
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9390179{col 45}{space 2}  .146099{col 56}{space 1}    6.43{col 65}{space 3}0.000{col 73}{space 4} .6523998{col 86}{space 3} 1.225636
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,787
                                                {txt}F(1, 1785)        =  {res}    11.27
                                                {txt}Prob > F          = {res}    0.0008
                                                {txt}R-squared         = {res}    0.0064
                                                {txt}Root MSE          =    {res} .49472

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1160391{col 26}{space 2} .0345653{col 37}{space 1}    3.36{col 46}{space 3}0.001{col 54}{space 4} .0482464{col 67}{space 3} .1838318
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4214609{col 26}{space 2} .0125615{col 37}{space 1}   33.55{col 46}{space 3}0.000{col 54}{space 4}  .396824{col 67}{space 3} .4460978
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,330
                                                {txt}F(42, 1287)       =  {res}    19.43
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2438
                                                {txt}Root MSE          =    {res} .44124

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0926252{col 45}{space 2}  .035684{col 56}{space 1}    2.60{col 65}{space 3}0.010{col 73}{space 4} .0226201{col 86}{space 3} .1626303
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0154905{col 45}{space 2} .0262436{col 56}{space 1}   -0.59{col 65}{space 3}0.555{col 73}{space 4}-.0669755{col 86}{space 3} .0359945
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}  .005449{col 45}{space 2} .0904164{col 56}{space 1}    0.06{col 65}{space 3}0.952{col 73}{space 4}-.1719307{col 86}{space 3} .1828287
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0059749{col 45}{space 2}  .057221{col 56}{space 1}    0.10{col 65}{space 3}0.917{col 73}{space 4}-.1062818{col 86}{space 3} .1182317
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0263418{col 45}{space 2} .0449747{col 56}{space 1}   -0.59{col 65}{space 3}0.558{col 73}{space 4}-.1145736{col 86}{space 3}   .06189
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0348462{col 45}{space 2} .0430486{col 56}{space 1}   -0.81{col 65}{space 3}0.418{col 73}{space 4}-.1192993{col 86}{space 3} .0496069
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0099547{col 45}{space 2} .0455583{col 56}{space 1}   -0.22{col 65}{space 3}0.827{col 73}{space 4}-.0993313{col 86}{space 3}  .079422
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0108558{col 45}{space 2} .0542799{col 56}{space 1}    0.20{col 65}{space 3}0.842{col 73}{space 4} -.095631{col 86}{space 3} .1173425
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0232927{col 45}{space 2} .0732933{col 56}{space 1}   -0.32{col 65}{space 3}0.751{col 73}{space 4}-.1670801{col 86}{space 3} .1204946
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1586387{col 45}{space 2} .1099448{col 56}{space 1}    1.44{col 65}{space 3}0.149{col 73}{space 4}-.0570521{col 86}{space 3} .3743294
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4173949{col 45}{space 2} .1796906{col 56}{space 1}   -2.32{col 65}{space 3}0.020{col 73}{space 4}-.7699136{col 86}{space 3}-.0648762
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0305631{col 45}{space 2} .2099149{col 56}{space 1}    0.15{col 65}{space 3}0.884{col 73}{space 4}-.3812497{col 86}{space 3}  .442376
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} -.001441{col 45}{space 2} .0045813{col 56}{space 1}   -0.31{col 65}{space 3}0.753{col 73}{space 4}-.0104287{col 86}{space 3} .0075467
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-6.22e-06{col 45}{space 2} .0000477{col 56}{space 1}   -0.13{col 65}{space 3}0.896{col 73}{space 4}-.0000998{col 86}{space 3} .0000874
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0544962{col 45}{space 2} .1049285{col 56}{space 1}   -0.52{col 65}{space 3}0.604{col 73}{space 4}-.2603459{col 86}{space 3} .1513534
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1284789{col 45}{space 2} .1061659{col 56}{space 1}   -1.21{col 65}{space 3}0.226{col 73}{space 4}-.3367562{col 86}{space 3} .0797984
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1588533{col 45}{space 2} .1078138{col 56}{space 1}   -1.47{col 65}{space 3}0.141{col 73}{space 4}-.3703633{col 86}{space 3} .0526567
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0781675{col 45}{space 2} .1069091{col 56}{space 1}   -0.73{col 65}{space 3}0.465{col 73}{space 4}-.2879027{col 86}{space 3} .1315677
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} -.094189{col 45}{space 2} .1085721{col 56}{space 1}   -0.87{col 65}{space 3}0.386{col 73}{space 4}-.3071867{col 86}{space 3} .1188086
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0036412{col 45}{space 2} .0596605{col 56}{space 1}    0.06{col 65}{space 3}0.951{col 73}{space 4}-.1134013{col 86}{space 3} .1206837
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1289942{col 45}{space 2} .0580016{col 56}{space 1}   -2.22{col 65}{space 3}0.026{col 73}{space 4}-.2427822{col 86}{space 3}-.0152062
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1777482{col 45}{space 2} .0643379{col 56}{space 1}   -2.76{col 65}{space 3}0.006{col 73}{space 4}-.3039668{col 86}{space 3}-.0515296
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2213782{col 45}{space 2} .0597517{col 56}{space 1}   -3.70{col 65}{space 3}0.000{col 73}{space 4}-.3385996{col 86}{space 3}-.1041568
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3857394{col 45}{space 2} .0679661{col 56}{space 1}   -5.68{col 65}{space 3}0.000{col 73}{space 4}-.5190759{col 86}{space 3}-.2524029
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2437062{col 45}{space 2} .0636807{col 56}{space 1}   -3.83{col 65}{space 3}0.000{col 73}{space 4}-.3686356{col 86}{space 3}-.1187768
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0251569{col 45}{space 2} .0689253{col 56}{space 1}   -0.36{col 65}{space 3}0.715{col 73}{space 4}-.1603751{col 86}{space 3} .1100613
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2294766{col 45}{space 2} .0727924{col 56}{space 1}   -3.15{col 65}{space 3}0.002{col 73}{space 4}-.3722814{col 86}{space 3}-.0866719
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1881114{col 45}{space 2}  .077782{col 56}{space 1}   -2.42{col 65}{space 3}0.016{col 73}{space 4}-.3407047{col 86}{space 3} -.035518
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} .3647258{col 45}{space 2} .0540684{col 56}{space 1}    6.75{col 65}{space 3}0.000{col 73}{space 4} .2586541{col 86}{space 3} .4707976
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0655266{col 45}{space 2} .0684782{col 56}{space 1}   -0.96{col 65}{space 3}0.339{col 73}{space 4}-.1998676{col 86}{space 3} .0688145
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}  .000997{col 45}{space 2} .0710452{col 56}{space 1}    0.01{col 65}{space 3}0.989{col 73}{space 4}-.1383801{col 86}{space 3} .1403741
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0413721{col 45}{space 2} .0712044{col 56}{space 1}    0.58{col 65}{space 3}0.561{col 73}{space 4}-.0983173{col 86}{space 3} .1810616
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4455302{col 45}{space 2} .0482088{col 56}{space 1}   -9.24{col 65}{space 3}0.000{col 73}{space 4}-.5401067{col 86}{space 3}-.3509536
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0838484{col 45}{space 2} .0545134{col 56}{space 1}   -1.54{col 65}{space 3}0.124{col 73}{space 4}-.1907934{col 86}{space 3} .0230965
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1498752{col 45}{space 2}  .061106{col 56}{space 1}    2.45{col 65}{space 3}0.014{col 73}{space 4} .0299968{col 86}{space 3} .2697535
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0341715{col 45}{space 2} .0721492{col 56}{space 1}   -0.47{col 65}{space 3}0.636{col 73}{space 4}-.1757144{col 86}{space 3} .1073714
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.4004781{col 45}{space 2} .0473101{col 56}{space 1}   -8.46{col 65}{space 3}0.000{col 73}{space 4}-.4932915{col 86}{space 3}-.3076646
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}  .131575{col 45}{space 2} .0664071{col 56}{space 1}    1.98{col 65}{space 3}0.048{col 73}{space 4}  .001297{col 86}{space 3}  .261853
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2096027{col 45}{space 2} .0908654{col 56}{space 1}   -2.31{col 65}{space 3}0.021{col 73}{space 4}-.3878633{col 86}{space 3}-.0313422
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1234027{col 45}{space 2} .0890483{col 56}{space 1}   -1.39{col 65}{space 3}0.166{col 73}{space 4}-.2980984{col 86}{space 3} .0512931
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0742415{col 45}{space 2} .1057225{col 56}{space 1}   -0.70{col 65}{space 3}0.483{col 73}{space 4}-.2816488{col 86}{space 3} .1331658
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1296378{col 45}{space 2} .1158219{col 56}{space 1}    1.12{col 65}{space 3}0.263{col 73}{space 4}-.0975825{col 86}{space 3} .3568582
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9234759{col 45}{space 2} .1464358{col 56}{space 1}    6.31{col 65}{space 3}0.000{col 73}{space 4} .6361969{col 86}{space 3} 1.210755
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,812
                                                {txt}F(1, 1810)        =  {res}    10.11
                                                {txt}Prob > F          = {res}    0.0015
                                                {txt}R-squared         = {res}    0.0056
                                                {txt}Root MSE          =    {res} .49461

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1080256{col 26}{space 2} .0339719{col 37}{space 1}    3.18{col 46}{space 3}0.001{col 54}{space 4} .0413974{col 67}{space 3} .1746538
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4199744{col 26}{space 2} .0124949{col 37}{space 1}   33.61{col 46}{space 3}0.000{col 54}{space 4} .3954684{col 67}{space 3} .4444804
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,339
                                                {txt}F(42, 1296)       =  {res}    20.02
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2483
                                                {txt}Root MSE          =    {res} .44006

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                     cabine_use{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}pp_dummy {c |}{col 33}{res}{space 2} .0944646{col 45}{space 2} .0352508{col 56}{space 1}    2.68{col 65}{space 3}0.007{col 73}{space 4} .0253096{col 86}{space 3} .1636195
{txt}{space 25}female {c |}{col 33}{res}{space 2}-.0085218{col 45}{space 2} .0260776{col 56}{space 1}   -0.33{col 65}{space 3}0.744{col 73}{space 4}-.0596808{col 86}{space 3} .0426372
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0061208{col 45}{space 2} .0925178{col 56}{space 1}   -0.07{col 65}{space 3}0.947{col 73}{space 4}-.1876219{col 86}{space 3} .1753803
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .001845{col 45}{space 2} .0568144{col 56}{space 1}    0.03{col 65}{space 3}0.974{col 73}{space 4}-.1096133{col 86}{space 3} .1133033
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}-.0256509{col 45}{space 2} .0448623{col 56}{space 1}   -0.57{col 65}{space 3}0.568{col 73}{space 4}-.1136616{col 86}{space 3} .0623598
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0320053{col 45}{space 2} .0428037{col 56}{space 1}   -0.75{col 65}{space 3}0.455{col 73}{space 4}-.1159775{col 86}{space 3} .0519669
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0136604{col 45}{space 2} .0449734{col 56}{space 1}   -0.30{col 65}{space 3}0.761{col 73}{space 4} -.101889{col 86}{space 3} .0745682
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} .0116773{col 45}{space 2} .0538427{col 56}{space 1}    0.22{col 65}{space 3}0.828{col 73}{space 4}-.0939512{col 86}{space 3} .1173058
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} -.019639{col 45}{space 2} .0731362{col 56}{space 1}   -0.27{col 65}{space 3}0.788{col 73}{space 4}-.1631172{col 86}{space 3} .1238393
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .1614857{col 45}{space 2} .1099356{col 56}{space 1}    1.47{col 65}{space 3}0.142{col 73}{space 4}-.0541855{col 86}{space 3}  .377157
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.4149853{col 45}{space 2} .1762946{col 56}{space 1}   -2.35{col 65}{space 3}0.019{col 73}{space 4}-.7608394{col 86}{space 3}-.0691312
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} .0347362{col 45}{space 2} .2104076{col 56}{space 1}    0.17{col 65}{space 3}0.869{col 73}{space 4}-.3780405{col 86}{space 3} .4475129
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0007609{col 45}{space 2} .0045473{col 56}{space 1}   -0.17{col 65}{space 3}0.867{col 73}{space 4}-.0096817{col 86}{space 3} .0081599
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} -.000015{col 45}{space 2} .0000473{col 56}{space 1}   -0.32{col 65}{space 3}0.751{col 73}{space 4}-.0001078{col 86}{space 3} .0000778
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0530253{col 45}{space 2} .1050443{col 56}{space 1}   -0.50{col 65}{space 3}0.614{col 73}{space 4}-.2591007{col 86}{space 3} .1530502
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1320083{col 45}{space 2}   .10604{col 56}{space 1}   -1.24{col 65}{space 3}0.213{col 73}{space 4}-.3400371{col 86}{space 3} .0760206
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1642774{col 45}{space 2} .1076561{col 56}{space 1}   -1.53{col 65}{space 3}0.127{col 73}{space 4}-.3754767{col 86}{space 3} .0469219
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0854382{col 45}{space 2}  .106881{col 56}{space 1}   -0.80{col 65}{space 3}0.424{col 73}{space 4}-.2951168{col 86}{space 3} .1242405
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} -.104385{col 45}{space 2} .1083642{col 56}{space 1}   -0.96{col 65}{space 3}0.336{col 73}{space 4}-.3169735{col 86}{space 3} .1082035
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0045119{col 45}{space 2} .0596175{col 56}{space 1}    0.08{col 65}{space 3}0.940{col 73}{space 4}-.1124455{col 86}{space 3} .1214692
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.1276892{col 45}{space 2} .0580009{col 56}{space 1}   -2.20{col 65}{space 3}0.028{col 73}{space 4}-.2414752{col 86}{space 3}-.0139032
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.1759072{col 45}{space 2} .0643246{col 56}{space 1}   -2.73{col 65}{space 3}0.006{col 73}{space 4}-.3020989{col 86}{space 3}-.0497154
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.2196068{col 45}{space 2} .0597512{col 56}{space 1}   -3.68{col 65}{space 3}0.000{col 73}{space 4}-.3368265{col 86}{space 3}-.1023871
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.3831659{col 45}{space 2} .0679115{col 56}{space 1}   -5.64{col 65}{space 3}0.000{col 73}{space 4}-.5163943{col 86}{space 3}-.2499374
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.2417345{col 45}{space 2} .0636864{col 56}{space 1}   -3.80{col 65}{space 3}0.000{col 73}{space 4}-.3666742{col 86}{space 3}-.1167949
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0240938{col 45}{space 2} .0689419{col 56}{space 1}   -0.35{col 65}{space 3}0.727{col 73}{space 4}-.1593438{col 86}{space 3} .1111563
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}-.2288289{col 45}{space 2} .0726663{col 56}{space 1}   -3.15{col 65}{space 3}0.002{col 73}{space 4}-.3713854{col 86}{space 3}-.0862724
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2}-.1879749{col 45}{space 2}  .077808{col 56}{space 1}   -2.42{col 65}{space 3}0.016{col 73}{space 4}-.3406184{col 86}{space 3}-.0353314
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}  .363629{col 45}{space 2} .0539247{col 56}{space 1}    6.74{col 65}{space 3}0.000{col 73}{space 4} .2578396{col 86}{space 3} .4694183
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0635115{col 45}{space 2} .0684994{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.1978934{col 86}{space 3} .0708704
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .0022629{col 45}{space 2} .0710423{col 56}{space 1}    0.03{col 65}{space 3}0.975{col 73}{space 4}-.1371076{col 86}{space 3} .1416333
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0425802{col 45}{space 2} .0712607{col 56}{space 1}    0.60{col 65}{space 3}0.550{col 73}{space 4}-.0972188{col 86}{space 3} .1823791
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.4440726{col 45}{space 2} .0482291{col 56}{space 1}   -9.21{col 65}{space 3}0.000{col 73}{space 4}-.5386883{col 86}{space 3}-.3494568
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0826274{col 45}{space 2} .0544514{col 56}{space 1}   -1.52{col 65}{space 3}0.129{col 73}{space 4}-.1894499{col 86}{space 3} .0241952
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .1510295{col 45}{space 2} .0611189{col 56}{space 1}    2.47{col 65}{space 3}0.014{col 73}{space 4} .0311268{col 86}{space 3} .2709322
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0334204{col 45}{space 2} .0721459{col 56}{space 1}   -0.46{col 65}{space 3}0.643{col 73}{space 4}-.1749559{col 86}{space 3} .1081152
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}-.3990542{col 45}{space 2} .0472944{col 56}{space 1}   -8.44{col 65}{space 3}0.000{col 73}{space 4}-.4918363{col 86}{space 3}-.3062722
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} .1322721{col 45}{space 2} .0663211{col 56}{space 1}    1.99{col 65}{space 3}0.046{col 73}{space 4} .0021635{col 86}{space 3} .2623806
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.2060898{col 45}{space 2} .0910235{col 56}{space 1}   -2.26{col 65}{space 3}0.024{col 73}{space 4}-.3846594{col 86}{space 3}-.0275203
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.1203588{col 45}{space 2} .0888437{col 56}{space 1}   -1.35{col 65}{space 3}0.176{col 73}{space 4}-.2946521{col 86}{space 3} .0539345
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0734897{col 45}{space 2} .1058948{col 56}{space 1}   -0.69{col 65}{space 3}0.488{col 73}{space 4}-.2812337{col 86}{space 3} .1342543
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .2548815{col 45}{space 2} .0875437{col 56}{space 1}    2.91{col 65}{space 3}0.004{col 73}{space 4} .0831386{col 86}{space 3} .4266244
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .9132764{col 45}{space 2} .1460377{col 56}{space 1}    6.25{col 65}{space 3}0.000{col 73}{space 4} .6267803{col 86}{space 3} 1.199773
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,830
                                                {txt}F(1, 1828)        =  {res}    10.68
                                                {txt}Prob > F          = {res}    0.0011
                                                {txt}R-squared         = {res}    0.0059
                                                {txt}Root MSE          =    {res} .49525

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}pp_dummy {c |}{col 14}{res}{space 2} .1104925{col 26}{space 2} .0338103{col 37}{space 1}    3.27{col 46}{space 3}0.001{col 54}{space 4} .0441816{col 67}{space 3} .1768034
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4252218{col 26}{space 2} .0124521{col 37}{space 1}   34.15{col 46}{space 3}0.000{col 54}{space 4}    .4008{col 67}{space 3} .4496436
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk.dta{rm}
saved
{p_end}

{com}. 
{txt}end of do-file

{com}. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_code/figured10_1.do"
{txt}
{com}. * Clean up
. clear all
{res}{txt}
{com}. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear
{txt}
{com}. 
. * Generate interaction
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
{txt}(2,957 missing values generated)

{com}. 
. * A fake model to start the dataset
. regr cabine_use CCAA

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,848
{txt}{hline 13}{c +}{hline 34}   F(1, 1846)      = {res}     4.17
{txt}       Model {c |} {res} 1.02665746         1  1.02665746   {txt}Prob > F        ={res}    0.0414
{txt}    Residual {c |} {res} 455.007433     1,846    .2464829   {txt}R-squared       ={res}    0.0023
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0017
{txt}       Total {c |} {res} 456.034091     1,847  .246905301   {txt}Root MSE        =   {res} .49647

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  cabine_use{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}CCAA {c |}{col 14}{res}{space 2}-.0046489{col 26}{space 2} .0022779{col 37}{space 1}   -2.04{col 46}{space 3}0.041{col 54}{space 4}-.0091163{col 67}{space 3}-.0001814
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4829034{col 26}{space 2} .0226314{col 37}{space 1}   21.34{col 46}{space 3}0.000{col 54}{space 4} .4385175{col 67}{space 3} .5272892
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regsave CCAA using 01_data/survey_ccaa_jk_2.dta, ci level(95) replace addlabel ///
> (Removed, fake, Model, fake, Controls, fake)
{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

{com}. 
. forvalues x = 1/19{c -(}
{txt}  2{com}.         regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income age age_sq i.education i.TAMUNI i.CCAA if CCAA != `x', r
{txt}  3{com}.         regsave cabine_use_pp_dummy using 01_data/survey_ccaa_jk_2.dta, ci level(95) append addlabel ///
> (Removed, `x', Model, uncomfortable, Controls, With controls)
{txt}  4{com}. 
.         regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy if CCAA != `x', r
{txt}  5{com}.         regsave cabine_use_pp_dummy using 01_data/survey_ccaa_jk_2.dta, ci level(95) append addlabel ///
> (Removed, `x', Model, uncomfortable, Controls, Without controls)
{txt}  6{com}. 
. {c )-}

{txt}Linear regression                               Number of obs     = {res}     1,125
                                                {txt}F(44, 1080)       =  {res}     2.02
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0883
                                                {txt}Root MSE          =    {res} .27608

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0070044{col 45}{space 2} .0180295{col 56}{space 1}   -0.39{col 65}{space 3}0.698{col 73}{space 4}-.0423812{col 86}{space 3} .0283725
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0324816{col 45}{space 2} .0353849{col 56}{space 1}   -0.92{col 65}{space 3}0.359{col 73}{space 4}-.1019125{col 86}{space 3} .0369493
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1307895{col 45}{space 2} .0550187{col 56}{space 1}    2.38{col 65}{space 3}0.018{col 73}{space 4} .0228338{col 86}{space 3} .2387452
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0301597{col 45}{space 2} .0171375{col 56}{space 1}    1.76{col 65}{space 3}0.079{col 73}{space 4}-.0034669{col 86}{space 3} .0637863
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0647427{col 45}{space 2} .0746581{col 56}{space 1}    0.87{col 65}{space 3}0.386{col 73}{space 4}-.0817487{col 86}{space 3}  .211234
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .1042461{col 45}{space 2}  .045653{col 56}{space 1}    2.28{col 65}{space 3}0.023{col 73}{space 4} .0146675{col 86}{space 3} .1938247
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0254071{col 45}{space 2} .0342889{col 56}{space 1}    0.74{col 65}{space 3}0.459{col 73}{space 4}-.0418733{col 86}{space 3} .0926876
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0240149{col 45}{space 2} .0303814{col 56}{space 1}    0.79{col 65}{space 3}0.429{col 73}{space 4}-.0355983{col 86}{space 3} .0836281
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0127271{col 45}{space 2} .0299307{col 56}{space 1}    0.43{col 65}{space 3}0.671{col 73}{space 4}-.0460018{col 86}{space 3}  .071456
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.030205{col 45}{space 2} .0323197{col 56}{space 1}   -0.93{col 65}{space 3}0.350{col 73}{space 4}-.0936216{col 86}{space 3} .0332116
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0139752{col 45}{space 2} .0475614{col 56}{space 1}   -0.29{col 65}{space 3}0.769{col 73}{space 4}-.1072985{col 86}{space 3}  .079348
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0922343{col 45}{space 2} .0775222{col 56}{space 1}    1.19{col 65}{space 3}0.234{col 73}{space 4}-.0598768{col 86}{space 3} .2443455
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0669221{col 45}{space 2} .0531927{col 56}{space 1}   -1.26{col 65}{space 3}0.209{col 73}{space 4}-.1712949{col 86}{space 3} .0374507
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0640743{col 45}{space 2} .0500951{col 56}{space 1}   -1.28{col 65}{space 3}0.201{col 73}{space 4}-.1623691{col 86}{space 3} .0342206
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}  .000143{col 45}{space 2} .0033295{col 56}{space 1}    0.04{col 65}{space 3}0.966{col 73}{space 4}  -.00639{col 86}{space 3}  .006676
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-7.84e-07{col 45}{space 2} .0000353{col 56}{space 1}   -0.02{col 65}{space 3}0.982{col 73}{space 4}  -.00007{col 86}{space 3} .0000685
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1238642{col 45}{space 2} .1257708{col 56}{space 1}   -0.98{col 65}{space 3}0.325{col 73}{space 4}-.3706471{col 86}{space 3} .1229186
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.1314701{col 45}{space 2} .1270375{col 56}{space 1}   -1.03{col 65}{space 3}0.301{col 73}{space 4}-.3807383{col 86}{space 3} .1177981
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1549182{col 45}{space 2} .1281201{col 56}{space 1}   -1.21{col 65}{space 3}0.227{col 73}{space 4}-.4063107{col 86}{space 3} .0964742
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1482678{col 45}{space 2} .1278291{col 56}{space 1}   -1.16{col 65}{space 3}0.246{col 73}{space 4}-.3990894{col 86}{space 3} .1025538
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1387329{col 45}{space 2} .1283005{col 56}{space 1}   -1.08{col 65}{space 3}0.280{col 73}{space 4}-.3904794{col 86}{space 3} .1130137
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .032195{col 45}{space 2} .0382183{col 56}{space 1}    0.84{col 65}{space 3}0.400{col 73}{space 4}-.0427956{col 86}{space 3} .1071856
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0198787{col 45}{space 2} .0330163{col 56}{space 1}    0.60{col 65}{space 3}0.547{col 73}{space 4}-.0449046{col 86}{space 3}  .084662
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0178312{col 45}{space 2}  .040557{col 56}{space 1}    0.44{col 65}{space 3}0.660{col 73}{space 4}-.0617483{col 86}{space 3} .0974106
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0057275{col 45}{space 2} .0349021{col 56}{space 1}   -0.16{col 65}{space 3}0.870{col 73}{space 4} -.074211{col 86}{space 3}  .062756
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0096477{col 45}{space 2} .0408557{col 56}{space 1}   -0.24{col 65}{space 3}0.813{col 73}{space 4}-.0898132{col 86}{space 3} .0705179
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1034206{col 45}{space 2}  .043053{col 56}{space 1}   -2.40{col 65}{space 3}0.016{col 73}{space 4}-.1878975{col 86}{space 3}-.0189437
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0880525{col 45}{space 2} .0605317{col 56}{space 1}    1.45{col 65}{space 3}0.146{col 73}{space 4}-.0307206{col 86}{space 3} .2068256
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0721245{col 45}{space 2} .0544869{col 56}{space 1}    1.32{col 65}{space 3}0.186{col 73}{space 4}-.0347877{col 86}{space 3} .1790368
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0370505{col 45}{space 2} .0437457{col 56}{space 1}   -0.85{col 65}{space 3}0.397{col 73}{space 4}-.1228868{col 86}{space 3} .0487858
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2} .0015287{col 45}{space 2} .0429599{col 56}{space 1}    0.04{col 65}{space 3}0.972{col 73}{space 4}-.0827656{col 86}{space 3}  .085823
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1556299{col 45}{space 2} .0654654{col 56}{space 1}    2.38{col 65}{space 3}0.018{col 73}{space 4} .0271762{col 86}{space 3} .2840836
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .1165076{col 45}{space 2} .0623052{col 56}{space 1}    1.87{col 65}{space 3}0.062{col 73}{space 4}-.0057454{col 86}{space 3} .2387607
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0502432{col 45}{space 2} .0428883{col 56}{space 1}    1.17{col 65}{space 3}0.242{col 73}{space 4}-.0339107{col 86}{space 3}  .134397
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} -.024796{col 45}{space 2} .0370273{col 56}{space 1}   -0.67{col 65}{space 3}0.503{col 73}{space 4}-.0974496{col 86}{space 3} .0478575
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} .0061832{col 45}{space 2} .0502593{col 56}{space 1}    0.12{col 65}{space 3}0.902{col 73}{space 4}-.0924336{col 86}{space 3} .1048001
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0556452{col 45}{space 2} .0385098{col 56}{space 1}   -1.44{col 65}{space 3}0.149{col 73}{space 4}-.1312076{col 86}{space 3} .0199173
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .1343281{col 45}{space 2} .0487667{col 56}{space 1}    2.75{col 65}{space 3}0.006{col 73}{space 4} .0386399{col 86}{space 3} .2300162
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0447648{col 45}{space 2} .0342438{col 56}{space 1}   -1.31{col 65}{space 3}0.191{col 73}{space 4}-.1119567{col 86}{space 3} .0224271
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2} .0246209{col 45}{space 2} .0605975{col 56}{space 1}    0.41{col 65}{space 3}0.685{col 73}{space 4}-.0942812{col 86}{space 3}  .143523
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0214006{col 45}{space 2} .0456081{col 56}{space 1}   -0.47{col 65}{space 3}0.639{col 73}{space 4}-.1108911{col 86}{space 3} .0680898
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0574793{col 45}{space 2} .0371135{col 56}{space 1}   -1.55{col 65}{space 3}0.122{col 73}{space 4} -.130302{col 86}{space 3} .0153433
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1190655{col 45}{space 2} .0861323{col 56}{space 1}    1.38{col 65}{space 3}0.167{col 73}{space 4}-.0499402{col 86}{space 3} .2880712
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0202323{col 45}{space 2} .0712832{col 56}{space 1}   -0.28{col 65}{space 3}0.777{col 73}{space 4}-.1601016{col 86}{space 3}  .119637
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1504193{col 45}{space 2} .1440194{col 56}{space 1}    1.04{col 65}{space 3}0.297{col 73}{space 4}-.1321702{col 86}{space 3} .4330088
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(note: variable
{bf:Removed} was str4 in the using data, but will be
byte now)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,554
                                                {txt}F(3, 1550)        =  {res}     2.70
                                                {txt}Prob > F          = {res}    0.0442
                                                {txt}R-squared         = {res}    0.0086
                                                {txt}Root MSE          =    {res} .29703

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0114342{col 33}{space 2} .0158752{col 44}{space 1}   -0.72{col 53}{space 3}0.471{col 61}{space 4}-.0425733{col 74}{space 3} .0197049
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0175257{col 33}{space 2} .0288797{col 44}{space 1}   -0.61{col 53}{space 3}0.544{col 61}{space 4}-.0741731{col 74}{space 3} .0391216
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1303395{col 33}{space 2} .0497855{col 44}{space 1}    2.62{col 53}{space 3}0.009{col 61}{space 4} .0326855{col 74}{space 3} .2279935
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .0967337{col 33}{space 2} .0104906{col 44}{space 1}    9.22{col 53}{space 3}0.000{col 61}{space 4} .0761564{col 74}{space 3} .1173109
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,298
                                                {txt}F(44, 1253)       =  {res}     2.32
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0775
                                                {txt}Root MSE          =    {res}  .2821

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0161033{col 45}{space 2} .0181351{col 56}{space 1}   -0.89{col 65}{space 3}0.375{col 73}{space 4}-.0516817{col 86}{space 3} .0194752
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0397641{col 45}{space 2} .0296385{col 56}{space 1}   -1.34{col 65}{space 3}0.180{col 73}{space 4}-.0979106{col 86}{space 3} .0183824
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1019231{col 45}{space 2} .0460939{col 56}{space 1}    2.21{col 65}{space 3}0.027{col 73}{space 4} .0114935{col 86}{space 3} .1923527
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0250148{col 45}{space 2} .0163932{col 56}{space 1}    1.53{col 65}{space 3}0.127{col 73}{space 4}-.0071464{col 86}{space 3} .0571759
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0018772{col 45}{space 2} .0600616{col 56}{space 1}   -0.03{col 65}{space 3}0.975{col 73}{space 4}-.1197096{col 86}{space 3} .1159553
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0862989{col 45}{space 2} .0411849{col 56}{space 1}    2.10{col 65}{space 3}0.036{col 73}{space 4}    .0055{col 86}{space 3} .1670978
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0169732{col 45}{space 2} .0309245{col 56}{space 1}    0.55{col 65}{space 3}0.583{col 73}{space 4}-.0436962{col 86}{space 3} .0776426
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}  .015556{col 45}{space 2}  .028605{col 56}{space 1}    0.54{col 65}{space 3}0.587{col 73}{space 4} -.040563{col 86}{space 3} .0716749
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0061002{col 45}{space 2} .0281259{col 56}{space 1}    0.22{col 65}{space 3}0.828{col 73}{space 4}-.0490787{col 86}{space 3} .0612792
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.038499{col 45}{space 2} .0311276{col 56}{space 1}   -1.24{col 65}{space 3}0.216{col 73}{space 4} -.099567{col 86}{space 3}  .022569
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}  -.02738{col 45}{space 2} .0428324{col 56}{space 1}   -0.64{col 65}{space 3}0.523{col 73}{space 4}-.1114111{col 86}{space 3}  .056651
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0666088{col 45}{space 2} .0719178{col 56}{space 1}    0.93{col 65}{space 3}0.355{col 73}{space 4}-.0744838{col 86}{space 3} .2077014
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0807269{col 45}{space 2} .0470685{col 56}{space 1}   -1.72{col 65}{space 3}0.087{col 73}{space 4}-.1730688{col 86}{space 3} .0116149
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.075983{col 45}{space 2} .0432943{col 56}{space 1}   -1.76{col 65}{space 3}0.079{col 73}{space 4}-.1609203{col 86}{space 3} .0089544
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0011034{col 45}{space 2} .0032132{col 56}{space 1}   -0.34{col 65}{space 3}0.731{col 73}{space 4}-.0074072{col 86}{space 3} .0052003
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000158{col 45}{space 2} .0000342{col 56}{space 1}    0.46{col 65}{space 3}0.643{col 73}{space 4}-.0000512{col 86}{space 3} .0000828
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0840881{col 45}{space 2} .0929996{col 56}{space 1}   -0.90{col 65}{space 3}0.366{col 73}{space 4}-.2665403{col 86}{space 3} .0983641
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0383772{col 45}{space 2}   .09501{col 56}{space 1}   -0.40{col 65}{space 3}0.686{col 73}{space 4}-.2247734{col 86}{space 3} .1480191
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0903516{col 45}{space 2} .0954975{col 56}{space 1}   -0.95{col 65}{space 3}0.344{col 73}{space 4}-.2777043{col 86}{space 3} .0970011
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0792829{col 45}{space 2} .0949966{col 56}{space 1}   -0.83{col 65}{space 3}0.404{col 73}{space 4}-.2656528{col 86}{space 3} .1070871
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0694564{col 45}{space 2} .0958619{col 56}{space 1}   -0.72{col 65}{space 3}0.469{col 73}{space 4} -.257524{col 86}{space 3} .1186112
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0587715{col 45}{space 2} .0398486{col 56}{space 1}    1.47{col 65}{space 3}0.140{col 73}{space 4}-.0194059{col 86}{space 3} .1369489
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0268647{col 45}{space 2} .0358685{col 56}{space 1}    0.75{col 65}{space 3}0.454{col 73}{space 4}-.0435042{col 86}{space 3} .0972337
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .012207{col 45}{space 2} .0407215{col 56}{space 1}    0.30{col 65}{space 3}0.764{col 73}{space 4}-.0676829{col 86}{space 3} .0920969
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0018723{col 45}{space 2} .0365205{col 56}{space 1}   -0.05{col 65}{space 3}0.959{col 73}{space 4}-.0735204{col 86}{space 3} .0697758
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0375148{col 45}{space 2} .0410563{col 56}{space 1}   -0.91{col 65}{space 3}0.361{col 73}{space 4}-.1180615{col 86}{space 3}  .043032
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1000867{col 45}{space 2} .0447435{col 56}{space 1}   -2.24{col 65}{space 3}0.025{col 73}{space 4} -.187867{col 86}{space 3}-.0123063
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0550168{col 45}{space 2} .0544203{col 56}{space 1}    1.01{col 65}{space 3}0.312{col 73}{space 4}-.0517481{col 86}{space 3} .1617818
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0530035{col 45}{space 2} .0517142{col 56}{space 1}    1.02{col 65}{space 3}0.306{col 73}{space 4}-.0484525{col 86}{space 3} .1544595
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0631052{col 45}{space 2} .0343968{col 56}{space 1}   -1.83{col 65}{space 3}0.067{col 73}{space 4}-.1305868{col 86}{space 3} .0043765
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0354785{col 45}{space 2} .0370034{col 56}{space 1}   -0.96{col 65}{space 3}0.338{col 73}{space 4} -.108074{col 86}{space 3}  .037117
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1276526{col 45}{space 2} .0597766{col 56}{space 1}    2.14{col 65}{space 3}0.033{col 73}{space 4} .0103793{col 86}{space 3} .2449259
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0858358{col 45}{space 2} .0555169{col 56}{space 1}    1.55{col 65}{space 3}0.122{col 73}{space 4}-.0230805{col 86}{space 3} .1947521
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0087677{col 45}{space 2} .0355047{col 56}{space 1}    0.25{col 65}{space 3}0.805{col 73}{space 4}-.0608875{col 86}{space 3} .0784229
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0543982{col 45}{space 2} .0275722{col 56}{space 1}   -1.97{col 65}{space 3}0.049{col 73}{space 4} -.108491{col 86}{space 3}-.0003053
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0194284{col 45}{space 2} .0436533{col 56}{space 1}   -0.45{col 65}{space 3}0.656{col 73}{space 4}  -.10507{col 86}{space 3} .0662132
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0945348{col 45}{space 2}  .028791{col 56}{space 1}   -3.28{col 65}{space 3}0.001{col 73}{space 4}-.1510185{col 86}{space 3} -.038051
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0967054{col 45}{space 2}  .041719{col 56}{space 1}    2.32{col 65}{space 3}0.021{col 73}{space 4} .0148585{col 86}{space 3} .1785522
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0636512{col 45}{space 2} .0249014{col 56}{space 1}   -2.56{col 65}{space 3}0.011{col 73}{space 4}-.1125043{col 86}{space 3} -.014798
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0180523{col 45}{space 2} .0562077{col 56}{space 1}   -0.32{col 65}{space 3}0.748{col 73}{space 4} -.128324{col 86}{space 3} .0922193
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0625012{col 45}{space 2} .0364225{col 56}{space 1}   -1.72{col 65}{space 3}0.086{col 73}{space 4} -.133957{col 86}{space 3} .0089546
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0910961{col 45}{space 2} .0263369{col 56}{space 1}   -3.46{col 65}{space 3}0.001{col 73}{space 4}-.1427654{col 86}{space 3}-.0394267
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0922987{col 45}{space 2} .0815315{col 56}{space 1}    1.13{col 65}{space 3}0.258{col 73}{space 4}-.0676546{col 86}{space 3} .2522521
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0324519{col 45}{space 2} .0644378{col 56}{space 1}   -0.50{col 65}{space 3}0.615{col 73}{space 4}-.1588698{col 86}{space 3}  .093966
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}  .145818{col 45}{space 2} .1126715{col 56}{space 1}    1.29{col 65}{space 3}0.196{col 73}{space 4}-.0752277{col 86}{space 3} .3668636
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,772
                                                {txt}F(3, 1768)        =  {res}     1.97
                                                {txt}Prob > F          = {res}    0.1163
                                                {txt}R-squared         = {res}    0.0046
                                                {txt}Root MSE          =    {res} .30323

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0081906{col 33}{space 2} .0153972{col 44}{space 1}   -0.53{col 53}{space 3}0.595{col 61}{space 4}-.0383893{col 74}{space 3}  .022008
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0252583{col 33}{space 2} .0267175{col 44}{space 1}   -0.95{col 53}{space 3}0.345{col 61}{space 4}-.0776596{col 74}{space 3}  .027143
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1016379{col 33}{space 2} .0435281{col 44}{space 1}    2.33{col 53}{space 3}0.020{col 61}{space 4} .0162659{col 74}{space 3}   .18701
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1021814{col 33}{space 2} .0102745{col 44}{space 1}    9.95{col 53}{space 3}0.000{col 61}{space 4} .0820299{col 74}{space 3} .1223329
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,306
                                                {txt}F(44, 1261)       =  {res}     2.27
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0786
                                                {txt}Root MSE          =    {res} .27682

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0159597{col 45}{space 2} .0175906{col 56}{space 1}   -0.91{col 65}{space 3}0.364{col 73}{space 4}-.0504698{col 86}{space 3} .0185504
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0505037{col 45}{space 2} .0280717{col 56}{space 1}   -1.80{col 65}{space 3}0.072{col 73}{space 4}-.1055761{col 86}{space 3} .0045688
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1121036{col 45}{space 2} .0445882{col 56}{space 1}    2.51{col 65}{space 3}0.012{col 73}{space 4} .0246284{col 86}{space 3} .1995788
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0323562{col 45}{space 2} .0159528{col 56}{space 1}    2.03{col 65}{space 3}0.043{col 73}{space 4} .0010593{col 86}{space 3} .0636532
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0014716{col 45}{space 2}  .059474{col 56}{space 1}    0.02{col 65}{space 3}0.980{col 73}{space 4}-.1152073{col 86}{space 3} .1181504
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0773002{col 45}{space 2} .0404233{col 56}{space 1}    1.91{col 65}{space 3}0.056{col 73}{space 4}-.0020042{col 86}{space 3} .1566046
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0161262{col 45}{space 2} .0308585{col 56}{space 1}    0.52{col 65}{space 3}0.601{col 73}{space 4}-.0444135{col 86}{space 3}  .076666
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0113869{col 45}{space 2} .0282307{col 56}{space 1}    0.40{col 65}{space 3}0.687{col 73}{space 4}-.0439973{col 86}{space 3} .0667712
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0158474{col 45}{space 2} .0283569{col 56}{space 1}    0.56{col 65}{space 3}0.576{col 73}{space 4}-.0397845{col 86}{space 3} .0714793
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0361727{col 45}{space 2} .0300058{col 56}{space 1}   -1.21{col 65}{space 3}0.228{col 73}{space 4}-.0950394{col 86}{space 3} .0226941
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0165687{col 45}{space 2} .0434993{col 56}{space 1}   -0.38{col 65}{space 3}0.703{col 73}{space 4}-.1019076{col 86}{space 3} .0687702
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0652364{col 45}{space 2} .0673126{col 56}{space 1}    0.97{col 65}{space 3}0.333{col 73}{space 4}-.0668205{col 86}{space 3} .1972933
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0777236{col 45}{space 2} .0476145{col 56}{space 1}   -1.63{col 65}{space 3}0.103{col 73}{space 4} -.171136{col 86}{space 3} .0156888
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0695216{col 45}{space 2} .0410792{col 56}{space 1}   -1.69{col 65}{space 3}0.091{col 73}{space 4}-.1501128{col 86}{space 3} .0110695
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0022042{col 45}{space 2} .0031744{col 56}{space 1}   -0.69{col 65}{space 3}0.488{col 73}{space 4}-.0084319{col 86}{space 3} .0040235
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000265{col 45}{space 2} .0000337{col 56}{space 1}    0.79{col 65}{space 3}0.431{col 73}{space 4}-.0000395{col 86}{space 3} .0000925
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0999136{col 45}{space 2}  .099327{col 56}{space 1}   -1.01{col 65}{space 3}0.315{col 73}{space 4}-.2947779{col 86}{space 3} .0949507
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0779207{col 45}{space 2} .1015327{col 56}{space 1}   -0.77{col 65}{space 3}0.443{col 73}{space 4}-.2771124{col 86}{space 3}  .121271
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2} -.112508{col 45}{space 2} .1021022{col 56}{space 1}   -1.10{col 65}{space 3}0.271{col 73}{space 4}-.3128168{col 86}{space 3} .0878009
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1025681{col 45}{space 2}  .101551{col 56}{space 1}   -1.01{col 65}{space 3}0.313{col 73}{space 4}-.3017956{col 86}{space 3} .0966593
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0952694{col 45}{space 2} .1022034{col 56}{space 1}   -0.93{col 65}{space 3}0.351{col 73}{space 4}-.2957768{col 86}{space 3}  .105238
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0566885{col 45}{space 2} .0373124{col 56}{space 1}    1.52{col 65}{space 3}0.129{col 73}{space 4}-.0165127{col 86}{space 3} .1298897
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0179976{col 45}{space 2} .0328136{col 56}{space 1}    0.55{col 65}{space 3}0.583{col 73}{space 4}-.0463776{col 86}{space 3} .0823729
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0001096{col 45}{space 2}  .037977{col 56}{space 1}   -0.00{col 65}{space 3}0.998{col 73}{space 4}-.0746147{col 86}{space 3} .0743954
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0083084{col 45}{space 2} .0339208{col 56}{space 1}   -0.24{col 65}{space 3}0.807{col 73}{space 4}-.0748557{col 86}{space 3} .0582389
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0405397{col 45}{space 2} .0362427{col 56}{space 1}   -1.12{col 65}{space 3}0.264{col 73}{space 4}-.1116424{col 86}{space 3}  .030563
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.107718{col 45}{space 2} .0427527{col 56}{space 1}   -2.52{col 65}{space 3}0.012{col 73}{space 4}-.1915923{col 86}{space 3}-.0238437
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0249033{col 45}{space 2}  .035807{col 56}{space 1}   -0.70{col 65}{space 3}0.487{col 73}{space 4}-.0951511{col 86}{space 3} .0453444
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0498676{col 45}{space 2} .0520083{col 56}{space 1}    0.96{col 65}{space 3}0.338{col 73}{space 4}-.0521647{col 86}{space 3} .1518999
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0616341{col 45}{space 2} .0343201{col 56}{space 1}   -1.80{col 65}{space 3}0.073{col 73}{space 4}-.1289649{col 86}{space 3} .0056967
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0376064{col 45}{space 2} .0368725{col 56}{space 1}   -1.02{col 65}{space 3}0.308{col 73}{space 4}-.1099445{col 86}{space 3} .0347317
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1276845{col 45}{space 2} .0597676{col 56}{space 1}    2.14{col 65}{space 3}0.033{col 73}{space 4} .0104296{col 86}{space 3} .2449394
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0806411{col 45}{space 2} .0553858{col 56}{space 1}    1.46{col 65}{space 3}0.146{col 73}{space 4}-.0280174{col 86}{space 3} .1892997
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0068401{col 45}{space 2} .0351328{col 56}{space 1}    0.19{col 65}{space 3}0.846{col 73}{space 4}-.0620852{col 86}{space 3} .0757654
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0548685{col 45}{space 2}  .027489{col 56}{space 1}   -2.00{col 65}{space 3}0.046{col 73}{space 4}-.1087977{col 86}{space 3}-.0009393
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} -.019232{col 45}{space 2} .0428498{col 56}{space 1}   -0.45{col 65}{space 3}0.654{col 73}{space 4}-.1032968{col 86}{space 3} .0648328
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0938755{col 45}{space 2} .0286288{col 56}{space 1}   -3.28{col 65}{space 3}0.001{col 73}{space 4}-.1500409{col 86}{space 3}-.0377101
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0974641{col 45}{space 2} .0414749{col 56}{space 1}    2.35{col 65}{space 3}0.019{col 73}{space 4} .0160967{col 86}{space 3} .1788315
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} -.065157{col 45}{space 2} .0248305{col 56}{space 1}   -2.62{col 65}{space 3}0.009{col 73}{space 4}-.1138705{col 86}{space 3}-.0164434
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0205165{col 45}{space 2} .0559564{col 56}{space 1}   -0.37{col 65}{space 3}0.714{col 73}{space 4}-.1302944{col 86}{space 3} .0892614
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0643869{col 45}{space 2} .0362126{col 56}{space 1}   -1.78{col 65}{space 3}0.076{col 73}{space 4}-.1354304{col 86}{space 3} .0066567
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0902945{col 45}{space 2} .0257706{col 56}{space 1}   -3.50{col 65}{space 3}0.000{col 73}{space 4}-.1408525{col 86}{space 3}-.0397365
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0982742{col 45}{space 2}    .0818{col 56}{space 1}    1.20{col 65}{space 3}0.230{col 73}{space 4}-.0622048{col 86}{space 3} .2587532
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0244978{col 45}{space 2} .0642677{col 56}{space 1}   -0.38{col 65}{space 3}0.703{col 73}{space 4}-.1505811{col 86}{space 3} .1015855
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .2004722{col 45}{space 2} .1163242{col 56}{space 1}    1.72{col 65}{space 3}0.085{col 73}{space 4}-.0277382{col 86}{space 3} .4286825
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,785
                                                {txt}F(3, 1781)        =  {res}     1.90
                                                {txt}Prob > F          = {res}    0.1273
                                                {txt}R-squared         = {res}    0.0042
                                                {txt}Root MSE          =    {res} .29783

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2} -.005332{col 33}{space 2} .0150919{col 44}{space 1}   -0.35{col 53}{space 3}0.724{col 61}{space 4}-.0349317{col 74}{space 3} .0242677
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0279118{col 33}{space 2} .0257917{col 44}{space 1}   -1.08{col 53}{space 3}0.279{col 61}{space 4}-.0784971{col 74}{space 3} .0226734
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .0975315{col 33}{space 2} .0423218{col 44}{space 1}    2.30{col 53}{space 3}0.021{col 61}{space 4} .0145258{col 74}{space 3} .1805372
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .0974771{col 33}{space 2} .0100556{col 44}{space 1}    9.69{col 53}{space 3}0.000{col 61}{space 4}  .077755{col 74}{space 3} .1171991
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,307
                                                {txt}F(44, 1262)       =  {res}     2.25
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0773
                                                {txt}Root MSE          =    {res} .27801

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0138119{col 45}{space 2} .0175902{col 56}{space 1}   -0.79{col 65}{space 3}0.432{col 73}{space 4}-.0483211{col 86}{space 3} .0206974
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0493527{col 45}{space 2} .0280981{col 56}{space 1}   -1.76{col 65}{space 3}0.079{col 73}{space 4}-.1044767{col 86}{space 3} .0057714
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2}  .114636{col 45}{space 2} .0452722{col 56}{space 1}    2.53{col 65}{space 3}0.011{col 73}{space 4} .0258189{col 86}{space 3}  .203453
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0254688{col 45}{space 2} .0160072{col 56}{space 1}    1.59{col 65}{space 3}0.112{col 73}{space 4} -.005935{col 86}{space 3} .0568725
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0276587{col 45}{space 2} .0660325{col 56}{space 1}    0.42{col 65}{space 3}0.675{col 73}{space 4}-.1018869{col 86}{space 3} .1572043
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0748218{col 45}{space 2}  .040847{col 56}{space 1}    1.83{col 65}{space 3}0.067{col 73}{space 4}-.0053138{col 86}{space 3} .1549573
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0126282{col 45}{space 2} .0308115{col 56}{space 1}    0.41{col 65}{space 3}0.682{col 73}{space 4}-.0478192{col 86}{space 3} .0730756
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0020209{col 45}{space 2} .0278458{col 56}{space 1}   -0.07{col 65}{space 3}0.942{col 73}{space 4}-.0566501{col 86}{space 3} .0526083
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0092856{col 45}{space 2} .0281975{col 56}{space 1}    0.33{col 65}{space 3}0.742{col 73}{space 4}-.0460336{col 86}{space 3} .0646048
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0364586{col 45}{space 2}  .030721{col 56}{space 1}   -1.19{col 65}{space 3}0.236{col 73}{space 4}-.0967285{col 86}{space 3} .0238113
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0215168{col 45}{space 2}  .045042{col 56}{space 1}   -0.48{col 65}{space 3}0.633{col 73}{space 4}-.1098823{col 86}{space 3} .0668488
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0644699{col 45}{space 2} .0698584{col 56}{space 1}    0.92{col 65}{space 3}0.356{col 73}{space 4}-.0725814{col 86}{space 3} .2015212
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0742989{col 45}{space 2} .0458789{col 56}{space 1}   -1.62{col 65}{space 3}0.106{col 73}{space 4}-.1643062{col 86}{space 3} .0157084
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2} -.075866{col 45}{space 2} .0412897{col 56}{space 1}   -1.84{col 65}{space 3}0.066{col 73}{space 4}-.1568701{col 86}{space 3} .0051381
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0007101{col 45}{space 2} .0032065{col 56}{space 1}   -0.22{col 65}{space 3}0.825{col 73}{space 4}-.0070007{col 86}{space 3} .0055805
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000113{col 45}{space 2} .0000342{col 56}{space 1}    0.33{col 65}{space 3}0.740{col 73}{space 4}-.0000557{col 86}{space 3} .0000784
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0935311{col 45}{space 2} .0957116{col 56}{space 1}   -0.98{col 65}{space 3}0.329{col 73}{space 4}-.2813024{col 86}{space 3} .0942403
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0634638{col 45}{space 2} .0977612{col 56}{space 1}   -0.65{col 65}{space 3}0.516{col 73}{space 4}-.2552561{col 86}{space 3} .1283285
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1061041{col 45}{space 2} .0982192{col 56}{space 1}   -1.08{col 65}{space 3}0.280{col 73}{space 4} -.298795{col 86}{space 3} .0865867
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1028246{col 45}{space 2} .0974556{col 56}{space 1}   -1.06{col 65}{space 3}0.292{col 73}{space 4}-.2940175{col 86}{space 3} .0883683
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0961762{col 45}{space 2} .0980906{col 56}{space 1}   -0.98{col 65}{space 3}0.327{col 73}{space 4}-.2886149{col 86}{space 3} .0962624
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0579432{col 45}{space 2} .0375411{col 56}{space 1}    1.54{col 65}{space 3}0.123{col 73}{space 4}-.0157067{col 86}{space 3} .1315931
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0125932{col 45}{space 2} .0330595{col 56}{space 1}    0.38{col 65}{space 3}0.703{col 73}{space 4}-.0522645{col 86}{space 3} .0774509
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0045828{col 45}{space 2} .0379727{col 56}{space 1}    0.12{col 65}{space 3}0.904{col 73}{space 4}-.0699138{col 86}{space 3} .0790794
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0084996{col 45}{space 2}  .034058{col 56}{space 1}   -0.25{col 65}{space 3}0.803{col 73}{space 4}-.0753162{col 86}{space 3}  .058317
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0261523{col 45}{space 2} .0359044{col 56}{space 1}   -0.73{col 65}{space 3}0.467{col 73}{space 4}-.0965912{col 86}{space 3} .0442866
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1056014{col 45}{space 2} .0429071{col 56}{space 1}   -2.46{col 65}{space 3}0.014{col 73}{space 4}-.1897784{col 86}{space 3}-.0214243
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} -.026199{col 45}{space 2} .0353344{col 56}{space 1}   -0.74{col 65}{space 3}0.459{col 73}{space 4}-.0955197{col 86}{space 3} .0431217
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2}  .058111{col 45}{space 2} .0545864{col 56}{space 1}    1.06{col 65}{space 3}0.287{col 73}{space 4}-.0489792{col 86}{space 3} .1652011
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0573983{col 45}{space 2}  .034654{col 56}{space 1}   -1.66{col 65}{space 3}0.098{col 73}{space 4} -.125384{col 86}{space 3} .0105874
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0332824{col 45}{space 2} .0367555{col 56}{space 1}   -0.91{col 65}{space 3}0.365{col 73}{space 4} -.105391{col 86}{space 3} .0388263
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1296795{col 45}{space 2} .0600428{col 56}{space 1}    2.16{col 65}{space 3}0.031{col 73}{space 4} .0118847{col 86}{space 3} .2474742
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0851978{col 45}{space 2} .0553901{col 56}{space 1}    1.54{col 65}{space 3}0.124{col 73}{space 4} -.023469{col 86}{space 3} .1938646
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0125357{col 45}{space 2} .0352531{col 56}{space 1}    0.36{col 65}{space 3}0.722{col 73}{space 4}-.0566255{col 86}{space 3} .0816969
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} -.053903{col 45}{space 2} .0275926{col 56}{space 1}   -1.95{col 65}{space 3}0.051{col 73}{space 4}-.1080354{col 86}{space 3} .0002294
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} -.018517{col 45}{space 2} .0431522{col 56}{space 1}   -0.43{col 65}{space 3}0.668{col 73}{space 4}-.1031749{col 86}{space 3} .0661409
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0885831{col 45}{space 2} .0288406{col 56}{space 1}   -3.07{col 65}{space 3}0.002{col 73}{space 4}-.1451639{col 86}{space 3}-.0320022
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .1024028{col 45}{space 2} .0415386{col 56}{space 1}    2.47{col 65}{space 3}0.014{col 73}{space 4} .0209105{col 86}{space 3} .1838952
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0652308{col 45}{space 2} .0245874{col 56}{space 1}   -2.65{col 65}{space 3}0.008{col 73}{space 4}-.1134674{col 86}{space 3}-.0169942
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0137439{col 45}{space 2} .0556947{col 56}{space 1}   -0.25{col 65}{space 3}0.805{col 73}{space 4}-.1230084{col 86}{space 3} .0955205
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0563033{col 45}{space 2} .0360676{col 56}{space 1}   -1.56{col 65}{space 3}0.119{col 73}{space 4}-.1270623{col 86}{space 3} .0144557
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0873802{col 45}{space 2} .0260434{col 56}{space 1}   -3.36{col 65}{space 3}0.001{col 73}{space 4}-.1384734{col 86}{space 3} -.036287
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0954327{col 45}{space 2}  .081369{col 56}{space 1}    1.17{col 65}{space 3}0.241{col 73}{space 4}-.0642008{col 86}{space 3} .2550661
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0270279{col 45}{space 2} .0639712{col 56}{space 1}   -0.42{col 65}{space 3}0.673{col 73}{space 4}-.1525296{col 86}{space 3} .0984738
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1659366{col 45}{space 2} .1141106{col 56}{space 1}    1.45{col 65}{space 3}0.146{col 73}{space 4}-.0579307{col 86}{space 3} .3898039
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,768
                                                {txt}F(3, 1764)        =  {res}     2.79
                                                {txt}Prob > F          = {res}    0.0391
                                                {txt}R-squared         = {res}    0.0063
                                                {txt}Root MSE          =    {res} .30104

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0085206{col 33}{space 2} .0152531{col 44}{space 1}   -0.56{col 53}{space 3}0.576{col 61}{space 4}-.0384366{col 74}{space 3} .0213954
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0364663{col 33}{space 2} .0256208{col 44}{space 1}   -1.42{col 53}{space 3}0.155{col 61}{space 4}-.0867167{col 74}{space 3} .0137841
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1234049{col 33}{space 2} .0434159{col 44}{space 1}    2.84{col 53}{space 3}0.005{col 61}{space 4} .0382528{col 74}{space 3}  .208557
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1006865{col 33}{space 2} .0101901{col 44}{space 1}    9.88{col 53}{space 3}0.000{col 61}{space 4} .0807006{col 74}{space 3} .1206724
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,316
                                                {txt}F(44, 1271)       =  {res}     2.36
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0769
                                                {txt}Root MSE          =    {res} .28249

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0168943{col 45}{space 2} .0176365{col 56}{space 1}   -0.96{col 65}{space 3}0.338{col 73}{space 4}-.0514942{col 86}{space 3} .0177057
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0384221{col 45}{space 2} .0296884{col 56}{space 1}   -1.29{col 65}{space 3}0.196{col 73}{space 4}-.0966658{col 86}{space 3} .0198215
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1087815{col 45}{space 2} .0465875{col 56}{space 1}    2.33{col 65}{space 3}0.020{col 73}{space 4} .0173846{col 86}{space 3} .2001784
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0277702{col 45}{space 2} .0162347{col 56}{space 1}    1.71{col 65}{space 3}0.087{col 73}{space 4}-.0040795{col 86}{space 3} .0596198
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0283034{col 45}{space 2} .0674252{col 56}{space 1}    0.42{col 65}{space 3}0.675{col 73}{space 4}-.1039734{col 86}{space 3} .1605803
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0845011{col 45}{space 2}  .041919{col 56}{space 1}    2.02{col 65}{space 3}0.044{col 73}{space 4}  .002263{col 86}{space 3} .1667391
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0096925{col 45}{space 2} .0313492{col 56}{space 1}    0.31{col 65}{space 3}0.757{col 73}{space 4}-.0518093{col 86}{space 3} .0711943
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0061774{col 45}{space 2} .0286111{col 56}{space 1}    0.22{col 65}{space 3}0.829{col 73}{space 4}-.0499527{col 86}{space 3} .0623076
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0056781{col 45}{space 2}  .028264{col 56}{space 1}    0.20{col 65}{space 3}0.841{col 73}{space 4}-.0497711{col 86}{space 3} .0611273
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0388371{col 45}{space 2} .0308882{col 56}{space 1}   -1.26{col 65}{space 3}0.209{col 73}{space 4}-.0994345{col 86}{space 3} .0217604
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0270166{col 45}{space 2} .0427892{col 56}{space 1}   -0.63{col 65}{space 3}0.528{col 73}{space 4}-.1109619{col 86}{space 3} .0569287
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0624659{col 45}{space 2} .0674366{col 56}{space 1}    0.93{col 65}{space 3}0.354{col 73}{space 4}-.0698333{col 86}{space 3} .1947652
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0769468{col 45}{space 2} .0467558{col 56}{space 1}   -1.65{col 65}{space 3}0.100{col 73}{space 4}-.1686739{col 86}{space 3} .0147804
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0730111{col 45}{space 2} .0419873{col 56}{space 1}   -1.74{col 65}{space 3}0.082{col 73}{space 4}-.1553831{col 86}{space 3} .0093609
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0010229{col 45}{space 2} .0031655{col 56}{space 1}   -0.32{col 65}{space 3}0.747{col 73}{space 4}-.0072332{col 86}{space 3} .0051873
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000152{col 45}{space 2} .0000335{col 56}{space 1}    0.46{col 65}{space 3}0.649{col 73}{space 4}-.0000505{col 86}{space 3} .0000809
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0800159{col 45}{space 2} .0925905{col 56}{space 1}   -0.86{col 65}{space 3}0.388{col 73}{space 4} -.261663{col 86}{space 3} .1016311
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0414534{col 45}{space 2} .0948368{col 56}{space 1}   -0.44{col 65}{space 3}0.662{col 73}{space 4}-.2275073{col 86}{space 3} .1446004
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0899134{col 45}{space 2} .0952394{col 56}{space 1}   -0.94{col 65}{space 3}0.345{col 73}{space 4}-.2767571{col 86}{space 3} .0969304
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0787877{col 45}{space 2} .0946625{col 56}{space 1}   -0.83{col 65}{space 3}0.405{col 73}{space 4}-.2644997{col 86}{space 3} .1069243
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} -.077095{col 45}{space 2} .0952909{col 56}{space 1}   -0.81{col 65}{space 3}0.419{col 73}{space 4}-.2640398{col 86}{space 3} .1098498
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0553205{col 45}{space 2} .0370904{col 56}{space 1}    1.49{col 65}{space 3}0.136{col 73}{space 4}-.0174448{col 86}{space 3} .1280857
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0202797{col 45}{space 2} .0327679{col 56}{space 1}    0.62{col 65}{space 3}0.536{col 73}{space 4}-.0440054{col 86}{space 3} .0845649
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0007193{col 45}{space 2} .0375677{col 56}{space 1}   -0.02{col 65}{space 3}0.985{col 73}{space 4}-.0744208{col 86}{space 3} .0729821
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0057752{col 45}{space 2} .0340921{col 56}{space 1}   -0.17{col 65}{space 3}0.866{col 73}{space 4}-.0726581{col 86}{space 3} .0611077
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.039111{col 45}{space 2} .0361032{col 56}{space 1}   -1.08{col 65}{space 3}0.279{col 73}{space 4}-.1099393{col 86}{space 3} .0317174
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1042663{col 45}{space 2} .0427443{col 56}{space 1}   -2.44{col 65}{space 3}0.015{col 73}{space 4}-.1881234{col 86}{space 3}-.0204091
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0213135{col 45}{space 2}   .03568{col 56}{space 1}   -0.60{col 65}{space 3}0.550{col 73}{space 4}-.0913117{col 86}{space 3} .0486848
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0563454{col 45}{space 2} .0541806{col 56}{space 1}    1.04{col 65}{space 3}0.299{col 73}{space 4}-.0499478{col 86}{space 3} .1626386
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0535157{col 45}{space 2} .0517736{col 56}{space 1}    1.03{col 65}{space 3}0.301{col 73}{space 4}-.0480554{col 86}{space 3} .1550869
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0355115{col 45}{space 2} .0364563{col 56}{space 1}   -0.97{col 65}{space 3}0.330{col 73}{space 4}-.1070327{col 86}{space 3} .0360097
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1276814{col 45}{space 2} .0598443{col 56}{space 1}    2.13{col 65}{space 3}0.033{col 73}{space 4}  .010277{col 86}{space 3} .2450859
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0846251{col 45}{space 2} .0552667{col 56}{space 1}    1.53{col 65}{space 3}0.126{col 73}{space 4}-.0237989{col 86}{space 3} .1930491
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0084892{col 45}{space 2}  .035212{col 56}{space 1}    0.24{col 65}{space 3}0.810{col 73}{space 4}-.0605908{col 86}{space 3} .0775693
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0547935{col 45}{space 2} .0276529{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4}-.1090439{col 86}{space 3} -.000543
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0202974{col 45}{space 2} .0433707{col 56}{space 1}   -0.47{col 65}{space 3}0.640{col 73}{space 4}-.1053834{col 86}{space 3} .0647885
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.093163{col 45}{space 2} .0285469{col 56}{space 1}   -3.26{col 65}{space 3}0.001{col 73}{space 4}-.1491673{col 86}{space 3}-.0371587
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0983595{col 45}{space 2} .0415352{col 56}{space 1}    2.37{col 65}{space 3}0.018{col 73}{space 4} .0168744{col 86}{space 3} .1798446
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0643834{col 45}{space 2} .0247102{col 56}{space 1}   -2.61{col 65}{space 3}0.009{col 73}{space 4}-.1128606{col 86}{space 3}-.0159061
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0160146{col 45}{space 2} .0558578{col 56}{space 1}   -0.29{col 65}{space 3}0.774{col 73}{space 4}-.1255983{col 86}{space 3}  .093569
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0604725{col 45}{space 2}   .03631{col 56}{space 1}   -1.67{col 65}{space 3}0.096{col 73}{space 4}-.1317067{col 86}{space 3} .0107617
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0923563{col 45}{space 2} .0259751{col 56}{space 1}   -3.56{col 65}{space 3}0.000{col 73}{space 4} -.143315{col 86}{space 3}-.0413977
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0986568{col 45}{space 2} .0810671{col 56}{space 1}    1.22{col 65}{space 3}0.224{col 73}{space 4}-.0603832{col 86}{space 3} .2576968
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0256489{col 45}{space 2} .0641994{col 56}{space 1}   -0.40{col 65}{space 3}0.690{col 73}{space 4}-.1515974{col 86}{space 3} .1002995
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1517356{col 45}{space 2} .1114362{col 56}{space 1}    1.36{col 65}{space 3}0.174{col 73}{space 4}-.0668835{col 86}{space 3} .3703547
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,796
                                                {txt}F(3, 1792)        =  {res}     2.23
                                                {txt}Prob > F          = {res}    0.0833
                                                {txt}R-squared         = {res}    0.0052
                                                {txt}Root MSE          =    {res} .30424

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0080476{col 33}{space 2} .0153859{col 44}{space 1}   -0.52{col 53}{space 3}0.601{col 61}{space 4}-.0382238{col 74}{space 3} .0221285
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0262646{col 33}{space 2} .0264591{col 44}{space 1}   -0.99{col 53}{space 3}0.321{col 61}{space 4}-.0781586{col 74}{space 3} .0256293
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2}  .108247{col 33}{space 2} .0436589{col 44}{space 1}    2.48{col 53}{space 3}0.013{col 61}{space 4} .0226192{col 74}{space 3} .1938748
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1025358{col 33}{space 2} .0100839{col 44}{space 1}   10.17{col 53}{space 3}0.000{col 61}{space 4} .0827585{col 74}{space 3} .1223132
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,288
                                                {txt}F(44, 1243)       =  {res}     2.30
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0757
                                                {txt}Root MSE          =    {res} .28232

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0152785{col 45}{space 2} .0181162{col 56}{space 1}   -0.84{col 65}{space 3}0.399{col 73}{space 4}-.0508202{col 86}{space 3} .0202632
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0365385{col 45}{space 2} .0317925{col 56}{space 1}   -1.15{col 65}{space 3}0.251{col 73}{space 4}-.0989113{col 86}{space 3} .0258343
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1150617{col 45}{space 2}  .049131{col 56}{space 1}    2.34{col 65}{space 3}0.019{col 73}{space 4} .0186728{col 86}{space 3} .2114506
{txt}{space 25}female {c |}{col 33}{res}{space 2}  .032325{col 45}{space 2} .0163267{col 56}{space 1}    1.98{col 65}{space 3}0.048{col 73}{space 4} .0002941{col 86}{space 3} .0643559
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0230593{col 45}{space 2} .0639815{col 56}{space 1}    0.36{col 65}{space 3}0.719{col 73}{space 4}-.1024643{col 86}{space 3}  .148583
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .062534{col 45}{space 2} .0400053{col 56}{space 1}    1.56{col 65}{space 3}0.118{col 73}{space 4}-.0159513{col 86}{space 3} .1410193
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0063759{col 45}{space 2} .0313018{col 56}{space 1}    0.20{col 65}{space 3}0.839{col 73}{space 4}-.0550343{col 86}{space 3} .0677861
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0140844{col 45}{space 2} .0296057{col 56}{space 1}    0.48{col 65}{space 3}0.634{col 73}{space 4}-.0439982{col 86}{space 3}  .072167
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0070486{col 45}{space 2}  .029109{col 56}{space 1}    0.24{col 65}{space 3}0.809{col 73}{space 4}-.0500597{col 86}{space 3} .0641569
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0379105{col 45}{space 2} .0316074{col 56}{space 1}   -1.20{col 65}{space 3}0.231{col 73}{space 4}-.0999202{col 86}{space 3} .0240993
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2} -.025539{col 45}{space 2} .0450485{col 56}{space 1}   -0.57{col 65}{space 3}0.571{col 73}{space 4}-.1139184{col 86}{space 3} .0628405
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0658039{col 45}{space 2} .0727622{col 56}{space 1}    0.90{col 65}{space 3}0.366{col 73}{space 4}-.0769463{col 86}{space 3} .2085542
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0774217{col 45}{space 2} .0484281{col 56}{space 1}   -1.60{col 65}{space 3}0.110{col 73}{space 4}-.1724315{col 86}{space 3} .0175881
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0806814{col 45}{space 2} .0479146{col 56}{space 1}   -1.68{col 65}{space 3}0.092{col 73}{space 4} -.174684{col 86}{space 3} .0133211
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0017997{col 45}{space 2} .0032776{col 56}{space 1}   -0.55{col 65}{space 3}0.583{col 73}{space 4}  -.00823{col 86}{space 3} .0046306
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}  .000023{col 45}{space 2} .0000348{col 56}{space 1}    0.66{col 65}{space 3}0.509{col 73}{space 4}-.0000453{col 86}{space 3} .0000913
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0751436{col 45}{space 2} .0931887{col 56}{space 1}   -0.81{col 65}{space 3}0.420{col 73}{space 4}-.2579682{col 86}{space 3}  .107681
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0476652{col 45}{space 2} .0955402{col 56}{space 1}   -0.50{col 65}{space 3}0.618{col 73}{space 4}-.2351032{col 86}{space 3} .1397728
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0844434{col 45}{space 2} .0960317{col 56}{space 1}   -0.88{col 65}{space 3}0.379{col 73}{space 4}-.2728456{col 86}{space 3} .1039588
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0777768{col 45}{space 2} .0954615{col 56}{space 1}   -0.81{col 65}{space 3}0.415{col 73}{space 4}-.2650603{col 86}{space 3} .1095067
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0706074{col 45}{space 2} .0961253{col 56}{space 1}   -0.73{col 65}{space 3}0.463{col 73}{space 4}-.2591931{col 86}{space 3} .1179783
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0458809{col 45}{space 2} .0420069{col 56}{space 1}    1.09{col 65}{space 3}0.275{col 73}{space 4}-.0365314{col 86}{space 3} .1282932
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0087911{col 45}{space 2} .0372741{col 56}{space 1}    0.24{col 65}{space 3}0.814{col 73}{space 4}-.0643359{col 86}{space 3} .0819182
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0030156{col 45}{space 2} .0423119{col 56}{space 1}   -0.07{col 65}{space 3}0.943{col 73}{space 4}-.0860262{col 86}{space 3}  .079995
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0140741{col 45}{space 2} .0383239{col 56}{space 1}   -0.37{col 65}{space 3}0.714{col 73}{space 4}-.0892606{col 86}{space 3} .0611125
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0484115{col 45}{space 2} .0393186{col 56}{space 1}   -1.23{col 65}{space 3}0.218{col 73}{space 4}-.1255497{col 86}{space 3} .0287267
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1130065{col 45}{space 2} .0455945{col 56}{space 1}   -2.48{col 65}{space 3}0.013{col 73}{space 4}-.2024573{col 86}{space 3}-.0235557
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0255737{col 45}{space 2} .0356046{col 56}{space 1}   -0.72{col 65}{space 3}0.473{col 73}{space 4}-.0954254{col 86}{space 3} .0442779
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0555532{col 45}{space 2} .0546532{col 56}{space 1}    1.02{col 65}{space 3}0.310{col 73}{space 4}-.0516695{col 86}{space 3} .1627759
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0522362{col 45}{space 2} .0517454{col 56}{space 1}    1.01{col 65}{space 3}0.313{col 73}{space 4}-.0492817{col 86}{space 3} .1537541
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0625802{col 45}{space 2} .0341828{col 56}{space 1}   -1.83{col 65}{space 3}0.067{col 73}{space 4}-.1296425{col 86}{space 3} .0044821
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}  .123993{col 45}{space 2} .0595354{col 56}{space 1}    2.08{col 65}{space 3}0.037{col 73}{space 4}  .007192{col 86}{space 3} .2407939
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}  .080115{col 45}{space 2} .0552447{col 56}{space 1}    1.45{col 65}{space 3}0.147{col 73}{space 4}-.0282681{col 86}{space 3} .1884981
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}  .008411{col 45}{space 2} .0353601{col 56}{space 1}    0.24{col 65}{space 3}0.812{col 73}{space 4} -.060961{col 86}{space 3}  .077783
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2} -.054462{col 45}{space 2} .0275927{col 56}{space 1}   -1.97{col 65}{space 3}0.049{col 73}{space 4}-.1085953{col 86}{space 3}-.0003287
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} -.022675{col 45}{space 2} .0435731{col 56}{space 1}   -0.52{col 65}{space 3}0.603{col 73}{space 4}  -.10816{col 86}{space 3} .0628099
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0928719{col 45}{space 2}  .028652{col 56}{space 1}   -3.24{col 65}{space 3}0.001{col 73}{space 4}-.1490836{col 86}{space 3}-.0366603
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0950696{col 45}{space 2} .0414657{col 56}{space 1}    2.29{col 65}{space 3}0.022{col 73}{space 4} .0137191{col 86}{space 3}   .17642
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0653896{col 45}{space 2} .0247502{col 56}{space 1}   -2.64{col 65}{space 3}0.008{col 73}{space 4}-.1139464{col 86}{space 3}-.0168327
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0166679{col 45}{space 2}  .056288{col 56}{space 1}   -0.30{col 65}{space 3}0.767{col 73}{space 4}-.1270979{col 86}{space 3}  .093762
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0607642{col 45}{space 2} .0361503{col 56}{space 1}   -1.68{col 65}{space 3}0.093{col 73}{space 4}-.1316865{col 86}{space 3} .0101581
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0948211{col 45}{space 2} .0260615{col 56}{space 1}   -3.64{col 65}{space 3}0.000{col 73}{space 4}-.1459506{col 86}{space 3}-.0436917
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .089495{col 45}{space 2}  .081713{col 56}{space 1}    1.10{col 65}{space 3}0.274{col 73}{space 4}-.0708156{col 86}{space 3} .2498055
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0360957{col 45}{space 2}  .065935{col 56}{space 1}   -0.55{col 65}{space 3}0.584{col 73}{space 4}-.1654519{col 86}{space 3} .0932604
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}  .173038{col 45}{space 2} .1141977{col 56}{space 1}    1.52{col 65}{space 3}0.130{col 73}{space 4}-.0510036{col 86}{space 3} .3970796
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,768
                                                {txt}F(3, 1764)        =  {res}     1.96
                                                {txt}Prob > F          = {res}    0.1183
                                                {txt}R-squared         = {res}    0.0048
                                                {txt}Root MSE          =    {res} .30349

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0056632{col 33}{space 2} .0153915{col 44}{space 1}   -0.37{col 53}{space 3}0.713{col 61}{space 4}-.0358506{col 74}{space 3} .0245242
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0195977{col 33}{space 2} .0278462{col 44}{space 1}   -0.70{col 53}{space 3}0.482{col 61}{space 4}-.0742127{col 74}{space 3} .0350174
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1001546{col 33}{space 2} .0449121{col 44}{space 1}    2.23{col 53}{space 3}0.026{col 61}{space 4} .0120681{col 74}{space 3} .1882411
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1006787{col 33}{space 2} .0101319{col 44}{space 1}    9.94{col 53}{space 3}0.000{col 61}{space 4} .0808069{col 74}{space 3} .1205506
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,300
                                                {txt}F(44, 1255)       =  {res}     2.07
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0706
                                                {txt}Root MSE          =    {res} .27195

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0281444{col 45}{space 2} .0174485{col 56}{space 1}   -1.61{col 65}{space 3}0.107{col 73}{space 4}-.0623758{col 86}{space 3} .0060871
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0407179{col 45}{space 2} .0302587{col 56}{space 1}   -1.35{col 65}{space 3}0.179{col 73}{space 4}-.1000812{col 86}{space 3} .0186453
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2}  .083916{col 45}{space 2} .0455381{col 56}{space 1}    1.84{col 65}{space 3}0.066{col 73}{space 4}-.0054232{col 86}{space 3} .1732551
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0292827{col 45}{space 2} .0156358{col 56}{space 1}    1.87{col 65}{space 3}0.061{col 73}{space 4}-.0013926{col 86}{space 3} .0599579
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0201592{col 45}{space 2} .0646147{col 56}{space 1}    0.31{col 65}{space 3}0.755{col 73}{space 4}-.1066055{col 86}{space 3} .1469239
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0774789{col 45}{space 2} .0409606{col 56}{space 1}    1.89{col 65}{space 3}0.059{col 73}{space 4}  -.00288{col 86}{space 3} .1578377
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} -.000113{col 45}{space 2} .0306618{col 56}{space 1}   -0.00{col 65}{space 3}0.997{col 73}{space 4}-.0602671{col 86}{space 3}  .060041
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}-.0134802{col 45}{space 2}  .027502{col 56}{space 1}   -0.49{col 65}{space 3}0.624{col 73}{space 4}-.0674352{col 86}{space 3} .0404748
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0025243{col 45}{space 2}  .028149{col 56}{space 1}    0.09{col 65}{space 3}0.929{col 73}{space 4}-.0526999{col 86}{space 3} .0577485
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0335851{col 45}{space 2}  .030479{col 56}{space 1}   -1.10{col 65}{space 3}0.271{col 73}{space 4}-.0933805{col 86}{space 3} .0262102
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0204042{col 45}{space 2} .0428844{col 56}{space 1}   -0.48{col 65}{space 3}0.634{col 73}{space 4}-.1045371{col 86}{space 3} .0637288
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0729006{col 45}{space 2} .0683981{col 56}{space 1}    1.07{col 65}{space 3}0.287{col 73}{space 4}-.0612866{col 86}{space 3} .2070879
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0870818{col 45}{space 2} .0445283{col 56}{space 1}   -1.96{col 65}{space 3}0.051{col 73}{space 4}  -.17444{col 86}{space 3} .0002763
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0801723{col 45}{space 2} .0422369{col 56}{space 1}   -1.90{col 65}{space 3}0.058{col 73}{space 4} -.163035{col 86}{space 3} .0026903
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0012772{col 45}{space 2} .0031533{col 56}{space 1}   -0.41{col 65}{space 3}0.686{col 73}{space 4}-.0074636{col 86}{space 3} .0049091
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000188{col 45}{space 2} .0000334{col 56}{space 1}    0.56{col 65}{space 3}0.575{col 73}{space 4}-.0000468{col 86}{space 3} .0000844
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} -.056361{col 45}{space 2} .0921189{col 56}{space 1}   -0.61{col 65}{space 3}0.541{col 73}{space 4}-.2370851{col 86}{space 3}  .124363
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0195669{col 45}{space 2} .0942068{col 56}{space 1}   -0.21{col 65}{space 3}0.835{col 73}{space 4} -.204387{col 86}{space 3} .1652533
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0680403{col 45}{space 2} .0949222{col 56}{space 1}   -0.72{col 65}{space 3}0.474{col 73}{space 4} -.254264{col 86}{space 3} .1181834
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0579542{col 45}{space 2} .0941681{col 56}{space 1}   -0.62{col 65}{space 3}0.538{col 73}{space 4}-.2426983{col 86}{space 3}   .12679
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0596088{col 45}{space 2} .0946576{col 56}{space 1}   -0.63{col 65}{space 3}0.529{col 73}{space 4}-.2453133{col 86}{space 3} .1260957
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .054487{col 45}{space 2} .0360198{col 56}{space 1}    1.51{col 65}{space 3}0.131{col 73}{space 4}-.0161788{col 86}{space 3} .1251527
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}  .023246{col 45}{space 2} .0313824{col 56}{space 1}    0.74{col 65}{space 3}0.459{col 73}{space 4}-.0383218{col 86}{space 3} .0848137
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0076522{col 45}{space 2} .0362964{col 56}{space 1}    0.21{col 65}{space 3}0.833{col 73}{space 4}-.0635561{col 86}{space 3} .0788604
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0077825{col 45}{space 2} .0326788{col 56}{space 1}   -0.24{col 65}{space 3}0.812{col 73}{space 4}-.0718937{col 86}{space 3} .0563286
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0416054{col 45}{space 2} .0351374{col 56}{space 1}   -1.18{col 65}{space 3}0.237{col 73}{space 4}  -.11054{col 86}{space 3} .0273292
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1038495{col 45}{space 2} .0418533{col 56}{space 1}   -2.48{col 65}{space 3}0.013{col 73}{space 4}-.1859597{col 86}{space 3}-.0217393
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}  -.02272{col 45}{space 2} .0356972{col 56}{space 1}   -0.64{col 65}{space 3}0.525{col 73}{space 4}-.0927528{col 86}{space 3} .0473128
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0515186{col 45}{space 2} .0542307{col 56}{space 1}    0.95{col 65}{space 3}0.342{col 73}{space 4}-.0548742{col 86}{space 3} .1579114
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0505497{col 45}{space 2} .0519149{col 56}{space 1}    0.97{col 65}{space 3}0.330{col 73}{space 4}-.0512999{col 86}{space 3} .1523994
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0578457{col 45}{space 2} .0347633{col 56}{space 1}   -1.66{col 65}{space 3}0.096{col 73}{space 4}-.1260462{col 86}{space 3} .0103549
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0362831{col 45}{space 2} .0362207{col 56}{space 1}   -1.00{col 65}{space 3}0.317{col 73}{space 4}-.1073429{col 86}{space 3} .0347768
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0848624{col 45}{space 2}  .055507{col 56}{space 1}    1.53{col 65}{space 3}0.127{col 73}{space 4}-.0240342{col 86}{space 3} .1937591
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0006135{col 45}{space 2} .0349608{col 56}{space 1}   -0.02{col 65}{space 3}0.986{col 73}{space 4}-.0692016{col 86}{space 3} .0679745
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0579626{col 45}{space 2} .0276514{col 56}{space 1}   -2.10{col 65}{space 3}0.036{col 73}{space 4}-.1122107{col 86}{space 3}-.0037145
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0141933{col 45}{space 2} .0431521{col 56}{space 1}   -0.33{col 65}{space 3}0.742{col 73}{space 4}-.0988514{col 86}{space 3} .0704649
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0949335{col 45}{space 2} .0285145{col 56}{space 1}   -3.33{col 65}{space 3}0.001{col 73}{space 4}-.1508748{col 86}{space 3}-.0389922
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0905092{col 45}{space 2} .0412973{col 56}{space 1}    2.19{col 65}{space 3}0.029{col 73}{space 4} .0094898{col 86}{space 3} .1715285
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0627034{col 45}{space 2} .0243273{col 56}{space 1}   -2.58{col 65}{space 3}0.010{col 73}{space 4}-.1104302{col 86}{space 3}-.0149767
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0199467{col 45}{space 2} .0559578{col 56}{space 1}   -0.36{col 65}{space 3}0.722{col 73}{space 4}-.1297279{col 86}{space 3} .0898346
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0650814{col 45}{space 2}  .036088{col 56}{space 1}   -1.80{col 65}{space 3}0.072{col 73}{space 4}-.1358808{col 86}{space 3} .0057181
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0911296{col 45}{space 2} .0256025{col 56}{space 1}   -3.56{col 65}{space 3}0.000{col 73}{space 4}-.1413581{col 86}{space 3}-.0409011
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0949799{col 45}{space 2} .0815513{col 56}{space 1}    1.16{col 65}{space 3}0.244{col 73}{space 4} -.065012{col 86}{space 3} .2549717
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0246175{col 45}{space 2} .0632696{col 56}{space 1}   -0.39{col 65}{space 3}0.697{col 73}{space 4}-.1487433{col 86}{space 3} .0995082
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1484758{col 45}{space 2} .1110819{col 56}{space 1}    1.34{col 65}{space 3}0.182{col 73}{space 4} -.069451{col 86}{space 3} .3664026
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,784
                                                {txt}F(3, 1780)        =  {res}     1.67
                                                {txt}Prob > F          = {res}    0.1720
                                                {txt}R-squared         = {res}    0.0031
                                                {txt}Root MSE          =    {res}  .2958

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0187694{col 33}{space 2}  .014941{col 44}{space 1}   -1.26{col 53}{space 3}0.209{col 61}{space 4}-.0480732{col 74}{space 3} .0105345
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0336896{col 33}{space 2} .0258506{col 44}{space 1}   -1.30{col 53}{space 3}0.193{col 61}{space 4}-.0843902{col 74}{space 3} .0170111
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .0909364{col 33}{space 2} .0418009{col 44}{space 1}    2.18{col 53}{space 3}0.030{col 61}{space 4} .0089524{col 74}{space 3} .1729204
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1032548{col 33}{space 2} .0102056{col 44}{space 1}   10.12{col 53}{space 3}0.000{col 61}{space 4} .0832386{col 74}{space 3}  .123271
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,302
                                                {txt}F(44, 1257)       =  {res}     2.17
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0738
                                                {txt}Root MSE          =    {res} .27464

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0170972{col 45}{space 2} .0175354{col 56}{space 1}   -0.98{col 65}{space 3}0.330{col 73}{space 4} -.051499{col 86}{space 3} .0173047
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0386735{col 45}{space 2} .0300545{col 56}{space 1}   -1.29{col 65}{space 3}0.198{col 73}{space 4} -.097636{col 86}{space 3} .0202889
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .0946733{col 45}{space 2} .0461153{col 56}{space 1}    2.05{col 65}{space 3}0.040{col 73}{space 4} .0042018{col 86}{space 3} .1851447
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0242797{col 45}{space 2} .0159217{col 56}{space 1}    1.52{col 65}{space 3}0.128{col 73}{space 4}-.0069563{col 86}{space 3} .0555158
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0249551{col 45}{space 2} .0639285{col 56}{space 1}    0.39{col 65}{space 3}0.696{col 73}{space 4}-.1004631{col 86}{space 3} .1503734
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0724101{col 45}{space 2} .0404434{col 56}{space 1}    1.79{col 65}{space 3}0.074{col 73}{space 4}-.0069339{col 86}{space 3} .1517541
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0066161{col 45}{space 2} .0302986{col 56}{space 1}    0.22{col 65}{space 3}0.827{col 73}{space 4}-.0528252{col 86}{space 3} .0660574
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0133192{col 45}{space 2} .0283659{col 56}{space 1}    0.47{col 65}{space 3}0.639{col 73}{space 4}-.0423305{col 86}{space 3}  .068969
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0066084{col 45}{space 2} .0279728{col 56}{space 1}    0.24{col 65}{space 3}0.813{col 73}{space 4}-.0482702{col 86}{space 3} .0614869
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.037308{col 45}{space 2} .0302116{col 56}{space 1}   -1.23{col 65}{space 3}0.217{col 73}{space 4}-.0965787{col 86}{space 3} .0219627
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0273064{col 45}{space 2} .0429411{col 56}{space 1}   -0.64{col 65}{space 3}0.525{col 73}{space 4}-.1115505{col 86}{space 3} .0569378
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0700549{col 45}{space 2} .0689984{col 56}{space 1}    1.02{col 65}{space 3}0.310{col 73}{space 4}-.0653099{col 86}{space 3} .2054196
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0849733{col 45}{space 2} .0442648{col 56}{space 1}   -1.92{col 65}{space 3}0.055{col 73}{space 4}-.1718144{col 86}{space 3} .0018677
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0809803{col 45}{space 2} .0424338{col 56}{space 1}   -1.91{col 65}{space 3}0.057{col 73}{space 4}-.1642292{col 86}{space 3} .0022687
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0012942{col 45}{space 2}   .00312{col 56}{space 1}   -0.41{col 65}{space 3}0.678{col 73}{space 4}-.0074153{col 86}{space 3} .0048268
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000173{col 45}{space 2} .0000331{col 56}{space 1}    0.52{col 65}{space 3}0.601{col 73}{space 4}-.0000476{col 86}{space 3} .0000822
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.1018374{col 45}{space 2} .0914652{col 56}{space 1}   -1.11{col 65}{space 3}0.266{col 73}{space 4}-.2812786{col 86}{space 3} .0776039
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0491133{col 45}{space 2} .0938121{col 56}{space 1}   -0.52{col 65}{space 3}0.601{col 73}{space 4}-.2331589{col 86}{space 3} .1349323
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0900164{col 45}{space 2} .0942746{col 56}{space 1}   -0.95{col 65}{space 3}0.340{col 73}{space 4}-.2749694{col 86}{space 3} .0949365
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0853004{col 45}{space 2} .0937241{col 56}{space 1}   -0.91{col 65}{space 3}0.363{col 73}{space 4}-.2691732{col 86}{space 3} .0985725
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0784929{col 45}{space 2} .0942936{col 56}{space 1}   -0.83{col 65}{space 3}0.405{col 73}{space 4} -.263483{col 86}{space 3} .1064972
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0818604{col 45}{space 2} .0339535{col 56}{space 1}    2.41{col 65}{space 3}0.016{col 73}{space 4} .0152485{col 86}{space 3} .1484722
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0486234{col 45}{space 2} .0295574{col 56}{space 1}    1.65{col 65}{space 3}0.100{col 73}{space 4} -.009364{col 86}{space 3} .1066107
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0442259{col 45}{space 2} .0357313{col 56}{space 1}    1.24{col 65}{space 3}0.216{col 73}{space 4}-.0258737{col 86}{space 3} .1143255
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0240678{col 45}{space 2} .0305318{col 56}{space 1}    0.79{col 65}{space 3}0.431{col 73}{space 4}-.0358311{col 86}{space 3} .0839666
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0133552{col 45}{space 2} .0338513{col 56}{space 1}   -0.39{col 65}{space 3}0.693{col 73}{space 4}-.0797664{col 86}{space 3} .0530559
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0743771{col 45}{space 2} .0401291{col 56}{space 1}   -1.85{col 65}{space 3}0.064{col 73}{space 4}-.1531045{col 86}{space 3} .0043503
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0153516{col 45}{space 2} .0357968{col 56}{space 1}   -0.43{col 65}{space 3}0.668{col 73}{space 4}-.0855797{col 86}{space 3} .0548765
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0516072{col 45}{space 2} .0542099{col 56}{space 1}    0.95{col 65}{space 3}0.341{col 73}{space 4}-.0547446{col 86}{space 3}  .157959
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0523085{col 45}{space 2} .0515796{col 56}{space 1}    1.01{col 65}{space 3}0.311{col 73}{space 4} -.048883{col 86}{space 3} .1535001
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0634566{col 45}{space 2} .0339931{col 56}{space 1}   -1.87{col 65}{space 3}0.062{col 73}{space 4}-.1301461{col 86}{space 3}  .003233
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0320337{col 45}{space 2} .0365236{col 56}{space 1}   -0.88{col 65}{space 3}0.381{col 73}{space 4}-.1036876{col 86}{space 3} .0396202
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1237922{col 45}{space 2} .0599174{col 56}{space 1}    2.07{col 65}{space 3}0.039{col 73}{space 4} .0062432{col 86}{space 3} .2413413
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0082161{col 45}{space 2} .0350711{col 56}{space 1}    0.23{col 65}{space 3}0.815{col 73}{space 4}-.0605882{col 86}{space 3} .0770203
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0547942{col 45}{space 2} .0275247{col 56}{space 1}   -1.99{col 65}{space 3}0.047{col 73}{space 4}-.1087937{col 86}{space 3}-.0007947
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0142075{col 45}{space 2} .0429291{col 56}{space 1}   -0.33{col 65}{space 3}0.741{col 73}{space 4} -.098428{col 86}{space 3} .0700131
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0934162{col 45}{space 2} .0285347{col 56}{space 1}   -3.27{col 65}{space 3}0.001{col 73}{space 4}-.1493972{col 86}{space 3}-.0374353
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}  .091493{col 45}{space 2} .0414613{col 56}{space 1}    2.21{col 65}{space 3}0.028{col 73}{space 4}  .010152{col 86}{space 3} .1728339
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0642187{col 45}{space 2} .0245524{col 56}{space 1}   -2.62{col 65}{space 3}0.009{col 73}{space 4}-.1123869{col 86}{space 3}-.0160506
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0145712{col 45}{space 2} .0561334{col 56}{space 1}   -0.26{col 65}{space 3}0.795{col 73}{space 4}-.1246965{col 86}{space 3} .0955542
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0620027{col 45}{space 2} .0371385{col 56}{space 1}   -1.67{col 65}{space 3}0.095{col 73}{space 4}-.1348629{col 86}{space 3} .0108575
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0912564{col 45}{space 2} .0255317{col 56}{space 1}   -3.57{col 65}{space 3}0.000{col 73}{space 4}-.1413458{col 86}{space 3}-.0411671
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0825015{col 45}{space 2} .0816804{col 56}{space 1}    1.01{col 65}{space 3}0.313{col 73}{space 4}-.0777434{col 86}{space 3} .2427464
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0414566{col 45}{space 2}  .065692{col 56}{space 1}   -0.63{col 65}{space 3}0.528{col 73}{space 4}-.1703346{col 86}{space 3} .0874214
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1388753{col 45}{space 2} .1079654{col 56}{space 1}    1.29{col 65}{space 3}0.199{col 73}{space 4}-.0729369{col 86}{space 3} .3506875
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,772
                                                {txt}F(3, 1768)        =  {res}     1.68
                                                {txt}Prob > F          = {res}    0.1696
                                                {txt}R-squared         = {res}    0.0035
                                                {txt}Root MSE          =    {res} .29662

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0107881{col 33}{space 2} .0150778{col 44}{space 1}   -0.72{col 53}{space 3}0.474{col 61}{space 4}-.0403603{col 74}{space 3} .0187842
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0292596{col 33}{space 2} .0259824{col 44}{space 1}   -1.13{col 53}{space 3}0.260{col 61}{space 4} -.080219{col 74}{space 3} .0216998
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .0944588{col 33}{space 2} .0424811{col 44}{space 1}    2.22{col 53}{space 3}0.026{col 61}{space 4} .0111403{col 74}{space 3} .1777772
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  .099435{col 33}{space 2} .0100704{col 44}{space 1}    9.87{col 53}{space 3}0.000{col 61}{space 4} .0796839{col 74}{space 3} .1191862
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,219
                                                {txt}{help j_robustsingular:F(43, 1174) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0852
                                                {txt}Root MSE          =    {res} .28152

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0102998{col 45}{space 2} .0184423{col 56}{space 1}   -0.56{col 65}{space 3}0.577{col 73}{space 4}-.0464834{col 86}{space 3} .0258838
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0346381{col 45}{space 2} .0309949{col 56}{space 1}   -1.12{col 65}{space 3}0.264{col 73}{space 4}-.0954498{col 86}{space 3} .0261735
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .0999594{col 45}{space 2} .0469139{col 56}{space 1}    2.13{col 65}{space 3}0.033{col 73}{space 4}  .007915{col 86}{space 3} .1920037
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0349565{col 45}{space 2} .0166263{col 56}{space 1}    2.10{col 65}{space 3}0.036{col 73}{space 4} .0023359{col 86}{space 3}  .067577
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0240631{col 45}{space 2} .0666416{col 56}{space 1}    0.36{col 65}{space 3}0.718{col 73}{space 4}-.1066868{col 86}{space 3} .1548131
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .081523{col 45}{space 2} .0428197{col 56}{space 1}    1.90{col 65}{space 3}0.057{col 73}{space 4}-.0024887{col 86}{space 3} .1655346
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0099354{col 45}{space 2} .0317208{col 56}{space 1}    0.31{col 65}{space 3}0.754{col 73}{space 4}-.0523003{col 86}{space 3} .0721712
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0125316{col 45}{space 2} .0296891{col 56}{space 1}    0.42{col 65}{space 3}0.673{col 73}{space 4} -.045718{col 86}{space 3} .0707813
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0012145{col 45}{space 2}  .029339{col 56}{space 1}    0.04{col 65}{space 3}0.967{col 73}{space 4}-.0563483{col 86}{space 3} .0587773
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0260041{col 45}{space 2} .0323594{col 56}{space 1}   -0.80{col 65}{space 3}0.422{col 73}{space 4}-.0894929{col 86}{space 3} .0374846
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0128428{col 45}{space 2} .0469871{col 56}{space 1}   -0.27{col 65}{space 3}0.785{col 73}{space 4}-.1050309{col 86}{space 3} .0793453
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0365215{col 45}{space 2} .0612693{col 56}{space 1}    0.60{col 65}{space 3}0.551{col 73}{space 4}-.0836881{col 86}{space 3} .1567311
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0139122{col 45}{space 2} .0527299{col 56}{space 1}   -0.26{col 65}{space 3}0.792{col 73}{space 4}-.1173675{col 86}{space 3} .0895431
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0763658{col 45}{space 2} .0444741{col 56}{space 1}   -1.72{col 65}{space 3}0.086{col 73}{space 4}-.1636234{col 86}{space 3} .0108918
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2} .0004043{col 45}{space 2} .0031345{col 56}{space 1}    0.13{col 65}{space 3}0.897{col 73}{space 4}-.0057456{col 86}{space 3} .0065543
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}-3.61e-06{col 45}{space 2}  .000032{col 56}{space 1}   -0.11{col 65}{space 3}0.910{col 73}{space 4}-.0000664{col 86}{space 3} .0000592
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0902325{col 45}{space 2} .1029793{col 56}{space 1}   -0.88{col 65}{space 3}0.381{col 73}{space 4}-.2922766{col 86}{space 3} .1118116
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0652334{col 45}{space 2} .1049506{col 56}{space 1}   -0.62{col 65}{space 3}0.534{col 73}{space 4}-.2711451{col 86}{space 3} .1406783
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1196633{col 45}{space 2}  .104874{col 56}{space 1}   -1.14{col 65}{space 3}0.254{col 73}{space 4}-.3254247{col 86}{space 3} .0860981
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.1124061{col 45}{space 2} .1041232{col 56}{space 1}   -1.08{col 65}{space 3}0.281{col 73}{space 4}-.3166945{col 86}{space 3} .0918822
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.1147274{col 45}{space 2} .1049364{col 56}{space 1}   -1.09{col 65}{space 3}0.274{col 73}{space 4}-.3206111{col 86}{space 3} .0911564
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0511324{col 45}{space 2} .0416518{col 56}{space 1}    1.23{col 65}{space 3}0.220{col 73}{space 4}-.0305879{col 86}{space 3} .1328527
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2}-.0038217{col 45}{space 2} .0367131{col 56}{space 1}   -0.10{col 65}{space 3}0.917{col 73}{space 4}-.0758523{col 86}{space 3} .0682089
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0039475{col 45}{space 2} .0420342{col 56}{space 1}   -0.09{col 65}{space 3}0.925{col 73}{space 4}-.0864181{col 86}{space 3} .0785231
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0201101{col 45}{space 2} .0389344{col 56}{space 1}   -0.52{col 65}{space 3}0.606{col 73}{space 4}-.0964989{col 86}{space 3} .0562787
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0478645{col 45}{space 2} .0396535{col 56}{space 1}   -1.21{col 65}{space 3}0.228{col 73}{space 4}-.1256641{col 86}{space 3} .0299352
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.159371{col 45}{space 2} .0613802{col 56}{space 1}   -2.60{col 65}{space 3}0.010{col 73}{space 4}-.2797981{col 86}{space 3}-.0389438
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0226508{col 45}{space 2} .0359868{col 56}{space 1}   -0.63{col 65}{space 3}0.529{col 73}{space 4}-.0932564{col 86}{space 3} .0479549
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0584786{col 45}{space 2} .0541047{col 56}{space 1}    1.08{col 65}{space 3}0.280{col 73}{space 4}-.0476742{col 86}{space 3} .1646314
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0564345{col 45}{space 2} .0521363{col 56}{space 1}    1.08{col 65}{space 3}0.279{col 73}{space 4}-.0458562{col 86}{space 3} .1587252
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0631442{col 45}{space 2} .0346428{col 56}{space 1}   -1.82{col 65}{space 3}0.069{col 73}{space 4}-.1311128{col 86}{space 3} .0048245
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0342099{col 45}{space 2} .0369628{col 56}{space 1}   -0.93{col 65}{space 3}0.355{col 73}{space 4}-.1067304{col 86}{space 3} .0383106
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1280956{col 45}{space 2} .0596559{col 56}{space 1}    2.15{col 65}{space 3}0.032{col 73}{space 4} .0110515{col 86}{space 3} .2451398
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0837334{col 45}{space 2} .0549721{col 56}{space 1}    1.52{col 65}{space 3}0.128{col 73}{space 4}-.0241212{col 86}{space 3}  .191588
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0517438{col 45}{space 2} .0278952{col 56}{space 1}   -1.85{col 65}{space 3}0.064{col 73}{space 4}-.1064738{col 86}{space 3} .0029862
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0247952{col 45}{space 2} .0440135{col 56}{space 1}   -0.56{col 65}{space 3}0.573{col 73}{space 4}-.1111491{col 86}{space 3} .0615588
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0906421{col 45}{space 2} .0287897{col 56}{space 1}   -3.15{col 65}{space 3}0.002{col 73}{space 4}-.1471271{col 86}{space 3}-.0341571
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .1180427{col 45}{space 2} .0462802{col 56}{space 1}    2.55{col 65}{space 3}0.011{col 73}{space 4} .0272416{col 86}{space 3} .2088437
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0599868{col 45}{space 2} .0248398{col 56}{space 1}   -2.41{col 65}{space 3}0.016{col 73}{space 4}-.1087221{col 86}{space 3}-.0112515
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0109971{col 45}{space 2} .0555235{col 56}{space 1}   -0.20{col 65}{space 3}0.843{col 73}{space 4}-.1199334{col 86}{space 3} .0979392
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0531878{col 45}{space 2} .0360395{col 56}{space 1}   -1.48{col 65}{space 3}0.140{col 73}{space 4}-.1238969{col 86}{space 3} .0175212
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0875439{col 45}{space 2} .0261015{col 56}{space 1}   -3.35{col 65}{space 3}0.001{col 73}{space 4}-.1387547{col 86}{space 3}-.0363331
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0925475{col 45}{space 2} .0808197{col 56}{space 1}    1.15{col 65}{space 3}0.252{col 73}{space 4}-.0660196{col 86}{space 3} .2511146
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0380238{col 45}{space 2} .0643763{col 56}{space 1}   -0.59{col 65}{space 3}0.555{col 73}{space 4}-.1643293{col 86}{space 3} .0882817
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1622129{col 45}{space 2} .1198321{col 56}{space 1}    1.35{col 65}{space 3}0.176{col 73}{space 4}-.0728962{col 86}{space 3}  .397322
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,585
                                                {txt}F(3, 1581)        =  {res}     2.43
                                                {txt}Prob > F          = {res}    0.0636
                                                {txt}R-squared         = {res}    0.0055
                                                {txt}Root MSE          =    {res} .31056

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0170324{col 33}{space 2} .0167423{col 44}{space 1}   -1.02{col 53}{space 3}0.309{col 61}{space 4}-.0498719{col 74}{space 3} .0158071
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0403417{col 33}{space 2}  .027609{col 44}{space 1}   -1.46{col 53}{space 3}0.144{col 61}{space 4}-.0944959{col 74}{space 3} .0138124
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1182182{col 33}{space 2} .0440299{col 44}{space 1}    2.68{col 53}{space 3}0.007{col 61}{space 4} .0318551{col 74}{space 3} .2045813
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  .113069{col 33}{space 2} .0121504{col 44}{space 1}    9.31{col 53}{space 3}0.000{col 61}{space 4} .0892364{col 74}{space 3} .1369017
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,231
                                                {txt}F(44, 1186)       =  {res}     2.32
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0812
                                                {txt}Root MSE          =    {res} .28641

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0116537{col 45}{space 2} .0191102{col 56}{space 1}   -0.61{col 65}{space 3}0.542{col 73}{space 4}-.0491472{col 86}{space 3} .0258398
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0306813{col 45}{space 2}  .032441{col 56}{space 1}   -0.95{col 65}{space 3}0.344{col 73}{space 4}-.0943295{col 86}{space 3}  .032967
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1033001{col 45}{space 2} .0494974{col 56}{space 1}    2.09{col 65}{space 3}0.037{col 73}{space 4}  .006188{col 86}{space 3} .2004122
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0267066{col 45}{space 2} .0169947{col 56}{space 1}    1.57{col 65}{space 3}0.116{col 73}{space 4}-.0066365{col 86}{space 3} .0600497
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0334635{col 45}{space 2} .0728549{col 56}{space 1}    0.46{col 65}{space 3}0.646{col 73}{space 4}-.1094753{col 86}{space 3} .1764024
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .1006484{col 45}{space 2} .0460654{col 56}{space 1}    2.18{col 65}{space 3}0.029{col 73}{space 4} .0102696{col 86}{space 3} .1910272
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0188939{col 45}{space 2} .0323187{col 56}{space 1}    0.58{col 65}{space 3}0.559{col 73}{space 4}-.0445143{col 86}{space 3} .0823021
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0091147{col 45}{space 2} .0294347{col 56}{space 1}    0.31{col 65}{space 3}0.757{col 73}{space 4}-.0486352{col 86}{space 3} .0668646
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}  .005702{col 45}{space 2} .0298546{col 56}{space 1}    0.19{col 65}{space 3}0.849{col 73}{space 4}-.0528717{col 86}{space 3} .0642758
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0338609{col 45}{space 2} .0320373{col 56}{space 1}   -1.06{col 65}{space 3}0.291{col 73}{space 4}-.0967169{col 86}{space 3} .0289952
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0213138{col 45}{space 2} .0456699{col 56}{space 1}   -0.47{col 65}{space 3}0.641{col 73}{space 4}-.1109166{col 86}{space 3} .0682889
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}  .075473{col 45}{space 2} .0702653{col 56}{space 1}    1.07{col 65}{space 3}0.283{col 73}{space 4}-.0623852{col 86}{space 3} .2133312
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0625799{col 45}{space 2} .0510059{col 56}{space 1}   -1.23{col 65}{space 3}0.220{col 73}{space 4}-.1626517{col 86}{space 3} .0374919
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0847928{col 45}{space 2} .0463361{col 56}{space 1}   -1.83{col 65}{space 3}0.068{col 73}{space 4}-.1757026{col 86}{space 3}  .006117
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0009454{col 45}{space 2} .0034135{col 56}{space 1}   -0.28{col 65}{space 3}0.782{col 73}{space 4}-.0076426{col 86}{space 3} .0057517
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000145{col 45}{space 2} .0000362{col 56}{space 1}    0.40{col 65}{space 3}0.690{col 73}{space 4}-.0000566{col 86}{space 3} .0000856
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0288695{col 45}{space 2}  .085417{col 56}{space 1}   -0.34{col 65}{space 3}0.735{col 73}{space 4}-.1964547{col 86}{space 3} .1387157
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} .0099776{col 45}{space 2} .0878336{col 56}{space 1}    0.11{col 65}{space 3}0.910{col 73}{space 4}-.1623488{col 86}{space 3} .1823041
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0363124{col 45}{space 2} .0882971{col 56}{space 1}   -0.41{col 65}{space 3}0.681{col 73}{space 4}-.2095483{col 86}{space 3} .1369236
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0264153{col 45}{space 2} .0878092{col 56}{space 1}   -0.30{col 65}{space 3}0.764{col 73}{space 4} -.198694{col 86}{space 3} .1458634
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0322777{col 45}{space 2} .0886004{col 56}{space 1}   -0.36{col 65}{space 3}0.716{col 73}{space 4}-.2061087{col 86}{space 3} .1415533
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0571494{col 45}{space 2} .0393753{col 56}{space 1}    1.45{col 65}{space 3}0.147{col 73}{space 4}-.0201035{col 86}{space 3} .1344023
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0247553{col 45}{space 2} .0350608{col 56}{space 1}    0.71{col 65}{space 3}0.480{col 73}{space 4}-.0440329{col 86}{space 3} .0935434
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0091124{col 45}{space 2} .0412361{col 56}{space 1}    0.22{col 65}{space 3}0.825{col 73}{space 4}-.0717914{col 86}{space 3} .0900163
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0137307{col 45}{space 2}  .035433{col 56}{space 1}   -0.39{col 65}{space 3}0.698{col 73}{space 4} -.083249{col 86}{space 3} .0557876
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0634138{col 45}{space 2} .0383293{col 56}{space 1}   -1.65{col 65}{space 3}0.098{col 73}{space 4}-.1386147{col 86}{space 3} .0117871
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1018593{col 45}{space 2} .0439927{col 56}{space 1}   -2.32{col 65}{space 3}0.021{col 73}{space 4}-.1881716{col 86}{space 3}-.0155471
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0149753{col 45}{space 2} .0356157{col 56}{space 1}   -0.42{col 65}{space 3}0.674{col 73}{space 4}-.0848521{col 86}{space 3} .0549015
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0566002{col 45}{space 2} .0539595{col 56}{space 1}    1.05{col 65}{space 3}0.294{col 73}{space 4}-.0492666{col 86}{space 3}  .162467
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0635848{col 45}{space 2} .0516554{col 56}{space 1}    1.23{col 65}{space 3}0.219{col 73}{space 4}-.0377614{col 86}{space 3} .1649309
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0678696{col 45}{space 2} .0352074{col 56}{space 1}   -1.93{col 65}{space 3}0.054{col 73}{space 4}-.1369454{col 86}{space 3} .0012062
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0407247{col 45}{space 2} .0367149{col 56}{space 1}   -1.11{col 65}{space 3}0.268{col 73}{space 4}-.1127581{col 86}{space 3} .0313088
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1225611{col 45}{space 2} .0601756{col 56}{space 1}    2.04{col 65}{space 3}0.042{col 73}{space 4} .0044985{col 86}{space 3} .2406236
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0806058{col 45}{space 2} .0554152{col 56}{space 1}    1.45{col 65}{space 3}0.146{col 73}{space 4} -.028117{col 86}{space 3} .1893285
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0073939{col 45}{space 2} .0356269{col 56}{space 1}    0.21{col 65}{space 3}0.836{col 73}{space 4} -.062505{col 86}{space 3} .0772927
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0262186{col 45}{space 2} .0439929{col 56}{space 1}   -0.60{col 65}{space 3}0.551{col 73}{space 4}-.1125312{col 86}{space 3} .0600941
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0987711{col 45}{space 2} .0287671{col 56}{space 1}   -3.43{col 65}{space 3}0.001{col 73}{space 4}-.1552111{col 86}{space 3}-.0423312
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}  .096082{col 45}{space 2}  .041833{col 56}{space 1}    2.30{col 65}{space 3}0.022{col 73}{space 4}  .014007{col 86}{space 3}  .178157
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0607195{col 45}{space 2} .0247508{col 56}{space 1}   -2.45{col 65}{space 3}0.014{col 73}{space 4}-.1092797{col 86}{space 3}-.0121593
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0185933{col 45}{space 2}   .05599{col 56}{space 1}   -0.33{col 65}{space 3}0.740{col 73}{space 4}-.1284439{col 86}{space 3} .0912572
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0612167{col 45}{space 2} .0367063{col 56}{space 1}   -1.67{col 65}{space 3}0.096{col 73}{space 4}-.1332333{col 86}{space 3} .0107998
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0937891{col 45}{space 2} .0270264{col 56}{space 1}   -3.47{col 65}{space 3}0.001{col 73}{space 4}-.1468139{col 86}{space 3}-.0407643
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0854874{col 45}{space 2} .0816541{col 56}{space 1}    1.05{col 65}{space 3}0.295{col 73}{space 4}-.0747153{col 86}{space 3}   .24569
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0412468{col 45}{space 2} .0649403{col 56}{space 1}   -0.64{col 65}{space 3}0.525{col 73}{space 4}-.1686575{col 86}{space 3} .0861639
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .0964848{col 45}{space 2} .1083843{col 56}{space 1}    0.89{col 65}{space 3}0.374{col 73}{space 4}-.1161617{col 86}{space 3} .3091312
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,706
                                                {txt}F(3, 1702)        =  {res}     2.26
                                                {txt}Prob > F          = {res}    0.0802
                                                {txt}R-squared         = {res}    0.0057
                                                {txt}Root MSE          =    {res} .30967

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0059318{col 33}{space 2} .0160066{col 44}{space 1}   -0.37{col 53}{space 3}0.711{col 61}{space 4}-.0373264{col 74}{space 3} .0254628
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0243692{col 33}{space 2}  .028015{col 44}{space 1}   -0.87{col 53}{space 3}0.384{col 61}{space 4}-.0793166{col 74}{space 3} .0305783
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1123507{col 33}{space 2} .0460652{col 44}{space 1}    2.44{col 53}{space 3}0.015{col 61}{space 4} .0220003{col 74}{space 3} .2027011
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1054502{col 33}{space 2} .0105844{col 44}{space 1}    9.96{col 53}{space 3}0.000{col 61}{space 4} .0846905{col 74}{space 3}   .12621
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,291
                                                {txt}{help j_robustsingular:F(43, 1246) }      =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0800
                                                {txt}Root MSE          =    {res}  .2792

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0128609{col 45}{space 2} .0175844{col 56}{space 1}   -0.73{col 65}{space 3}0.465{col 73}{space 4}-.0473592{col 86}{space 3} .0216375
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2} -.037702{col 45}{space 2} .0298694{col 56}{space 1}   -1.26{col 65}{space 3}0.207{col 73}{space 4}-.0963018{col 86}{space 3} .0208978
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1151371{col 45}{space 2} .0481271{col 56}{space 1}    2.39{col 65}{space 3}0.017{col 73}{space 4}  .020718{col 86}{space 3} .2095563
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0313969{col 45}{space 2} .0159884{col 56}{space 1}    1.96{col 65}{space 3}0.050{col 73}{space 4} .0000297{col 86}{space 3} .0627641
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0411508{col 45}{space 2} .0717074{col 56}{space 1}    0.57{col 65}{space 3}0.566{col 73}{space 4}-.0995298{col 86}{space 3} .1818314
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0787635{col 45}{space 2} .0416954{col 56}{space 1}    1.89{col 65}{space 3}0.059{col 73}{space 4}-.0030374{col 86}{space 3} .1605645
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0073525{col 45}{space 2} .0310058{col 56}{space 1}    0.24{col 65}{space 3}0.813{col 73}{space 4}-.0534768{col 86}{space 3} .0681818
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0150057{col 45}{space 2} .0293616{col 56}{space 1}    0.51{col 65}{space 3}0.609{col 73}{space 4}-.0425979{col 86}{space 3} .0726094
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0017405{col 45}{space 2} .0280678{col 56}{space 1}    0.06{col 65}{space 3}0.951{col 73}{space 4}-.0533248{col 86}{space 3} .0568058
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2} -.036145{col 45}{space 2} .0306682{col 56}{space 1}   -1.18{col 65}{space 3}0.239{col 73}{space 4} -.096312{col 86}{space 3}  .024022
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0255873{col 45}{space 2} .0433873{col 56}{space 1}   -0.59{col 65}{space 3}0.555{col 73}{space 4}-.1107076{col 86}{space 3} .0595329
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0607633{col 45}{space 2} .0677047{col 56}{space 1}    0.90{col 65}{space 3}0.370{col 73}{space 4}-.0720646{col 86}{space 3} .1935912
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.118411{col 45}{space 2}  .043577{col 56}{space 1}   -2.72{col 65}{space 3}0.007{col 73}{space 4}-.2039034{col 86}{space 3}-.0329186
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0686039{col 45}{space 2} .0418398{col 56}{space 1}   -1.64{col 65}{space 3}0.101{col 73}{space 4}-.1506881{col 86}{space 3} .0134803
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0007601{col 45}{space 2} .0031571{col 56}{space 1}   -0.24{col 65}{space 3}0.810{col 73}{space 4}-.0069539{col 86}{space 3} .0054337
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2}  .000013{col 45}{space 2} .0000333{col 56}{space 1}    0.39{col 65}{space 3}0.697{col 73}{space 4}-.0000524{col 86}{space 3} .0000784
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0289304{col 45}{space 2} .0855439{col 56}{space 1}   -0.34{col 65}{space 3}0.735{col 73}{space 4}-.1967563{col 86}{space 3} .1388955
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2} .0120055{col 45}{space 2} .0874269{col 56}{space 1}    0.14{col 65}{space 3}0.891{col 73}{space 4}-.1595146{col 86}{space 3} .1835257
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0485093{col 45}{space 2} .0873921{col 56}{space 1}   -0.56{col 65}{space 3}0.579{col 73}{space 4}-.2199612{col 86}{space 3} .1229427
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0339436{col 45}{space 2} .0869884{col 56}{space 1}   -0.39{col 65}{space 3}0.696{col 73}{space 4}-.2046035{col 86}{space 3} .1367164
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0282611{col 45}{space 2} .0870024{col 56}{space 1}   -0.32{col 65}{space 3}0.745{col 73}{space 4}-.1989485{col 86}{space 3} .1424263
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0275879{col 45}{space 2} .0397686{col 56}{space 1}    0.69{col 65}{space 3}0.488{col 73}{space 4} -.050433{col 86}{space 3} .1056088
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0064697{col 45}{space 2} .0362988{col 56}{space 1}    0.18{col 65}{space 3}0.859{col 73}{space 4}-.0647437{col 86}{space 3} .0776832
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0183069{col 45}{space 2} .0403441{col 56}{space 1}   -0.45{col 65}{space 3}0.650{col 73}{space 4}-.0974569{col 86}{space 3}  .060843
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0200312{col 45}{space 2} .0379051{col 56}{space 1}   -0.53{col 65}{space 3}0.597{col 73}{space 4} -.094396{col 86}{space 3} .0543336
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2} -.054359{col 45}{space 2} .0387299{col 56}{space 1}   -1.40{col 65}{space 3}0.161{col 73}{space 4} -.130342{col 86}{space 3} .0216239
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1206523{col 45}{space 2} .0451083{col 56}{space 1}   -2.67{col 65}{space 3}0.008{col 73}{space 4}-.2091489{col 86}{space 3}-.0321558
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0257935{col 45}{space 2} .0356671{col 56}{space 1}   -0.72{col 65}{space 3}0.470{col 73}{space 4}-.0957677{col 86}{space 3} .0441807
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0573055{col 45}{space 2} .0536175{col 56}{space 1}    1.07{col 65}{space 3}0.285{col 73}{space 4} -.047885{col 86}{space 3}  .162496
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0520978{col 45}{space 2} .0513123{col 56}{space 1}    1.02{col 65}{space 3}0.310{col 73}{space 4}-.0485702{col 86}{space 3} .1527658
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0684425{col 45}{space 2} .0346333{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4}-.1363885{col 86}{space 3}-.0004965
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0372997{col 45}{space 2} .0367135{col 56}{space 1}   -1.02{col 65}{space 3}0.310{col 73}{space 4}-.1093269{col 86}{space 3} .0347275
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2}  .126509{col 45}{space 2} .0596802{col 56}{space 1}    2.12{col 65}{space 3}0.034{col 73}{space 4} .0094243{col 86}{space 3} .2435938
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0818377{col 45}{space 2} .0548578{col 56}{space 1}    1.49{col 65}{space 3}0.136{col 73}{space 4}-.0257863{col 86}{space 3} .1894616
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0090557{col 45}{space 2} .0354348{col 56}{space 1}    0.26{col 65}{space 3}0.798{col 73}{space 4}-.0604627{col 86}{space 3} .0785742
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0555254{col 45}{space 2} .0278547{col 56}{space 1}   -1.99{col 65}{space 3}0.046{col 73}{space 4}-.1101727{col 86}{space 3}-.0008781
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0926734{col 45}{space 2} .0284231{col 56}{space 1}   -3.26{col 65}{space 3}0.001{col 73}{space 4}-.1484359{col 86}{space 3} -.036911
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2}  .098651{col 45}{space 2}  .041658{col 56}{space 1}    2.37{col 65}{space 3}0.018{col 73}{space 4} .0169235{col 86}{space 3} .1803786
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0673656{col 45}{space 2} .0246615{col 56}{space 1}   -2.73{col 65}{space 3}0.006{col 73}{space 4}-.1157482{col 86}{space 3} -.018983
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0143342{col 45}{space 2} .0559152{col 56}{space 1}   -0.26{col 65}{space 3}0.798{col 73}{space 4}-.1240325{col 86}{space 3}  .095364
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0614091{col 45}{space 2} .0358701{col 56}{space 1}   -1.71{col 65}{space 3}0.087{col 73}{space 4}-.1317815{col 86}{space 3} .0089633
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0956822{col 45}{space 2} .0261621{col 56}{space 1}   -3.66{col 65}{space 3}0.000{col 73}{space 4}-.1470089{col 86}{space 3}-.0443556
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0960706{col 45}{space 2} .0810361{col 56}{space 1}    1.19{col 65}{space 3}0.236{col 73}{space 4}-.0629117{col 86}{space 3} .2550528
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0305512{col 45}{space 2}  .065522{col 56}{space 1}   -0.47{col 65}{space 3}0.641{col 73}{space 4}-.1590969{col 86}{space 3} .0979945
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1102741{col 45}{space 2} .1056207{col 56}{space 1}    1.04{col 65}{space 3}0.297{col 73}{space 4}-.0969399{col 86}{space 3}  .317488
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,775
                                                {txt}F(3, 1771)        =  {res}     2.33
                                                {txt}Prob > F          = {res}    0.0727
                                                {txt}R-squared         = {res}    0.0058
                                                {txt}Root MSE          =    {res} .30282

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0089408{col 33}{space 2} .0153069{col 44}{space 1}   -0.58{col 53}{space 3}0.559{col 61}{space 4}-.0389624{col 74}{space 3} .0210807
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0239763{col 33}{space 2} .0268406{col 44}{space 1}   -0.89{col 53}{space 3}0.372{col 61}{space 4}-.0766188{col 74}{space 3} .0286662
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1138943{col 33}{space 2} .0451619{col 44}{space 1}    2.52{col 53}{space 3}0.012{col 61}{space 4}  .025318{col 74}{space 3} .2024706
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1015625{col 33}{space 2} .0101029{col 44}{space 1}   10.05{col 53}{space 3}0.000{col 61}{space 4} .0817476{col 74}{space 3} .1213774
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,294
                                                {txt}F(44, 1249)       =  {res}     2.33
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0763
                                                {txt}Root MSE          =    {res} .28482

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0181106{col 45}{space 2} .0183702{col 56}{space 1}   -0.99{col 65}{space 3}0.324{col 73}{space 4}-.0541504{col 86}{space 3} .0179292
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0390344{col 45}{space 2} .0314794{col 56}{space 1}   -1.24{col 65}{space 3}0.215{col 73}{space 4}-.1007928{col 86}{space 3}  .022724
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1071485{col 45}{space 2}  .047698{col 56}{space 1}    2.25{col 65}{space 3}0.025{col 73}{space 4} .0135714{col 86}{space 3} .2007255
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0282403{col 45}{space 2} .0164409{col 56}{space 1}    1.72{col 65}{space 3}0.086{col 73}{space 4}-.0040146{col 86}{space 3} .0604952
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0264711{col 45}{space 2} .0661431{col 56}{space 1}    0.40{col 65}{space 3}0.689{col 73}{space 4}-.1032927{col 86}{space 3} .1562349
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0858652{col 45}{space 2} .0435081{col 56}{space 1}    1.97{col 65}{space 3}0.049{col 73}{space 4} .0005081{col 86}{space 3} .1712223
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}  .003881{col 45}{space 2} .0318701{col 56}{space 1}    0.12{col 65}{space 3}0.903{col 73}{space 4}-.0586439{col 86}{space 3} .0664059
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0129611{col 45}{space 2} .0299102{col 56}{space 1}    0.43{col 65}{space 3}0.665{col 73}{space 4}-.0457187{col 86}{space 3} .0716408
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0073722{col 45}{space 2}   .02933{col 56}{space 1}    0.25{col 65}{space 3}0.802{col 73}{space 4}-.0501694{col 86}{space 3} .0649138
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0386218{col 45}{space 2}  .031377{col 56}{space 1}   -1.23{col 65}{space 3}0.219{col 73}{space 4}-.1001792{col 86}{space 3} .0229356
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0263584{col 45}{space 2} .0438921{col 56}{space 1}   -0.60{col 65}{space 3}0.548{col 73}{space 4}-.1124687{col 86}{space 3}  .059752
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0625142{col 45}{space 2} .0702435{col 56}{space 1}    0.89{col 65}{space 3}0.374{col 73}{space 4}-.0752941{col 86}{space 3} .2003226
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0756438{col 45}{space 2} .0474633{col 56}{space 1}   -1.59{col 65}{space 3}0.111{col 73}{space 4}-.1687603{col 86}{space 3} .0174727
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0770828{col 45}{space 2}   .04362{col 56}{space 1}   -1.77{col 65}{space 3}0.077{col 73}{space 4}-.1626594{col 86}{space 3} .0084937
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}  -.00155{col 45}{space 2} .0033495{col 56}{space 1}   -0.46{col 65}{space 3}0.644{col 73}{space 4}-.0081213{col 86}{space 3} .0050213
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000211{col 45}{space 2} .0000357{col 56}{space 1}    0.59{col 65}{space 3}0.555{col 73}{space 4} -.000049{col 86}{space 3} .0000911
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0924696{col 45}{space 2} .1006346{col 56}{space 1}   -0.92{col 65}{space 3}0.358{col 73}{space 4}-.2899011{col 86}{space 3} .1049619
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0562333{col 45}{space 2} .1028832{col 56}{space 1}   -0.55{col 65}{space 3}0.585{col 73}{space 4}-.2580761{col 86}{space 3} .1456096
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.1052195{col 45}{space 2} .1033769{col 56}{space 1}   -1.02{col 65}{space 3}0.309{col 73}{space 4}-.3080309{col 86}{space 3}  .097592
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}  -.09848{col 45}{space 2}  .102534{col 56}{space 1}   -0.96{col 65}{space 3}0.337{col 73}{space 4}-.2996379{col 86}{space 3} .1026779
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0889031{col 45}{space 2} .1034717{col 56}{space 1}   -0.86{col 65}{space 3}0.390{col 73}{space 4}-.2919006{col 86}{space 3} .1140943
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0624492{col 45}{space 2} .0393385{col 56}{space 1}    1.59{col 65}{space 3}0.113{col 73}{space 4}-.0147276{col 86}{space 3}  .139626
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0185809{col 45}{space 2} .0342612{col 56}{space 1}    0.54{col 65}{space 3}0.588{col 73}{space 4}-.0486349{col 86}{space 3} .0857967
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}  .007524{col 45}{space 2} .0393546{col 56}{space 1}    0.19{col 65}{space 3}0.848{col 73}{space 4}-.0696843{col 86}{space 3} .0847324
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0069389{col 45}{space 2} .0354439{col 56}{space 1}   -0.20{col 65}{space 3}0.845{col 73}{space 4} -.076475{col 86}{space 3} .0625972
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0382554{col 45}{space 2} .0372258{col 56}{space 1}   -1.03{col 65}{space 3}0.304{col 73}{space 4}-.1112874{col 86}{space 3} .0347766
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1039425{col 45}{space 2} .0435939{col 56}{space 1}   -2.38{col 65}{space 3}0.017{col 73}{space 4}-.1894679{col 86}{space 3}-.0184171
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0212474{col 45}{space 2} .0358163{col 56}{space 1}   -0.59{col 65}{space 3}0.553{col 73}{space 4}-.0915142{col 86}{space 3} .0490195
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0573999{col 45}{space 2} .0542986{col 56}{space 1}    1.06{col 65}{space 3}0.291{col 73}{space 4}-.0491266{col 86}{space 3} .1639263
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0528803{col 45}{space 2} .0517636{col 56}{space 1}    1.02{col 65}{space 3}0.307{col 73}{space 4}-.0486729{col 86}{space 3} .1544335
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0588842{col 45}{space 2} .0344932{col 56}{space 1}   -1.71{col 65}{space 3}0.088{col 73}{space 4}-.1265552{col 86}{space 3} .0087868
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2} -.035249{col 45}{space 2} .0366246{col 56}{space 1}   -0.96{col 65}{space 3}0.336{col 73}{space 4}-.1071015{col 86}{space 3} .0366036
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1268382{col 45}{space 2}  .059749{col 56}{space 1}    2.12{col 65}{space 3}0.034{col 73}{space 4} .0096188{col 86}{space 3} .2440576
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0843794{col 45}{space 2} .0553921{col 56}{space 1}    1.52{col 65}{space 3}0.128{col 73}{space 4}-.0242924{col 86}{space 3} .1930511
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0089425{col 45}{space 2} .0353168{col 56}{space 1}    0.25{col 65}{space 3}0.800{col 73}{space 4}-.0603444{col 86}{space 3} .0782294
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0547859{col 45}{space 2} .0276434{col 56}{space 1}   -1.98{col 65}{space 3}0.048{col 73}{space 4}-.1090186{col 86}{space 3}-.0005533
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0211475{col 45}{space 2} .0432316{col 56}{space 1}   -0.49{col 65}{space 3}0.625{col 73}{space 4}-.1059621{col 86}{space 3} .0636671
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0970896{col 45}{space 2} .0415836{col 56}{space 1}    2.33{col 65}{space 3}0.020{col 73}{space 4} .0155081{col 86}{space 3} .1786711
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0621402{col 45}{space 2} .0248077{col 56}{space 1}   -2.50{col 65}{space 3}0.012{col 73}{space 4}-.1108096{col 86}{space 3}-.0134708
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0172572{col 45}{space 2} .0561857{col 56}{space 1}   -0.31{col 65}{space 3}0.759{col 73}{space 4}-.1274859{col 86}{space 3} .0929714
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0582703{col 45}{space 2} .0364647{col 56}{space 1}   -1.60{col 65}{space 3}0.110{col 73}{space 4}-.1298091{col 86}{space 3} .0132685
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0900588{col 45}{space 2} .0261674{col 56}{space 1}   -3.44{col 65}{space 3}0.001{col 73}{space 4}-.1413957{col 86}{space 3} -.038722
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0921661{col 45}{space 2} .0814999{col 56}{space 1}    1.13{col 65}{space 3}0.258{col 73}{space 4}-.0677258{col 86}{space 3}  .252058
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0322337{col 45}{space 2}  .064595{col 56}{space 1}   -0.50{col 65}{space 3}0.618{col 73}{space 4}-.1589603{col 86}{space 3} .0944929
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}   .17488{col 45}{space 2} .1194024{col 56}{space 1}    1.46{col 65}{space 3}0.143{col 73}{space 4}-.0593714{col 86}{space 3} .4091315
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,764
                                                {txt}F(3, 1760)        =  {res}     2.03
                                                {txt}Prob > F          = {res}    0.1080
                                                {txt}R-squared         = {res}    0.0048
                                                {txt}Root MSE          =    {res} .30527

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0094531{col 33}{space 2} .0155015{col 44}{space 1}   -0.61{col 53}{space 3}0.542{col 61}{space 4}-.0398564{col 74}{space 3} .0209501
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0225636{col 33}{space 2} .0279072{col 44}{space 1}   -0.81{col 53}{space 3}0.419{col 61}{space 4}-.0772983{col 74}{space 3} .0321712
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1022851{col 33}{space 2} .0442322{col 44}{space 1}    2.31{col 53}{space 3}0.021{col 61}{space 4} .0155319{col 74}{space 3} .1890383
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1036446{col 33}{space 2} .0102982{col 44}{space 1}   10.06{col 53}{space 3}0.000{col 61}{space 4} .0834468{col 74}{space 3} .1238425
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,204
                                                {txt}F(44, 1159)       =  {res}     2.17
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0832
                                                {txt}Root MSE          =    {res} .26932

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0135077{col 45}{space 2} .0178912{col 56}{space 1}   -0.75{col 65}{space 3}0.450{col 73}{space 4}-.0486104{col 86}{space 3} .0215951
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2} -.029964{col 45}{space 2} .0295878{col 56}{space 1}   -1.01{col 65}{space 3}0.311{col 73}{space 4}-.0880156{col 86}{space 3} .0280876
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .0826409{col 45}{space 2} .0452206{col 56}{space 1}    1.83{col 65}{space 3}0.068{col 73}{space 4}-.0060825{col 86}{space 3} .1713643
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0211498{col 45}{space 2} .0162025{col 56}{space 1}    1.31{col 65}{space 3}0.192{col 73}{space 4}-.0106398{col 86}{space 3} .0529394
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0477586{col 45}{space 2} .0686997{col 56}{space 1}    0.70{col 65}{space 3}0.487{col 73}{space 4} -.087031{col 86}{space 3} .1825482
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0726167{col 45}{space 2} .0405683{col 56}{space 1}    1.79{col 65}{space 3}0.074{col 73}{space 4}-.0069788{col 86}{space 3} .1522122
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0060408{col 45}{space 2} .0307707{col 56}{space 1}    0.20{col 65}{space 3}0.844{col 73}{space 4}-.0543317{col 86}{space 3} .0664134
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}  .021493{col 45}{space 2} .0297494{col 56}{space 1}    0.72{col 65}{space 3}0.470{col 73}{space 4}-.0368757{col 86}{space 3} .0798618
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}-.0072343{col 45}{space 2} .0280372{col 56}{space 1}   -0.26{col 65}{space 3}0.796{col 73}{space 4}-.0622437{col 86}{space 3} .0477751
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0554456{col 45}{space 2}  .030339{col 56}{space 1}   -1.83{col 65}{space 3}0.068{col 73}{space 4}-.1149712{col 86}{space 3} .0040799
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0809385{col 45}{space 2} .0300379{col 56}{space 1}   -2.69{col 65}{space 3}0.007{col 73}{space 4}-.1398733{col 86}{space 3}-.0220037
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2}-.0178209{col 45}{space 2} .0541746{col 56}{space 1}   -0.33{col 65}{space 3}0.742{col 73}{space 4}-.1241123{col 86}{space 3} .0884704
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.083319{col 45}{space 2} .0448562{col 56}{space 1}   -1.86{col 65}{space 3}0.063{col 73}{space 4}-.1713275{col 86}{space 3} .0046896
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0591734{col 45}{space 2} .0409093{col 56}{space 1}   -1.45{col 65}{space 3}0.148{col 73}{space 4}-.1394381{col 86}{space 3} .0210912
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0000201{col 45}{space 2} .0032648{col 56}{space 1}   -0.01{col 65}{space 3}0.995{col 73}{space 4}-.0064257{col 86}{space 3} .0063854
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} 9.16e-06{col 45}{space 2} .0000348{col 56}{space 1}    0.26{col 65}{space 3}0.793{col 73}{space 4}-.0000592{col 86}{space 3} .0000775
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0791977{col 45}{space 2} .0932193{col 56}{space 1}   -0.85{col 65}{space 3}0.396{col 73}{space 4}-.2620951{col 86}{space 3} .1036998
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0228123{col 45}{space 2} .0960587{col 56}{space 1}   -0.24{col 65}{space 3}0.812{col 73}{space 4}-.2112807{col 86}{space 3} .1656561
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0821099{col 45}{space 2} .0964361{col 56}{space 1}   -0.85{col 65}{space 3}0.395{col 73}{space 4}-.2713187{col 86}{space 3} .1070989
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0574161{col 45}{space 2} .0959997{col 56}{space 1}   -0.60{col 65}{space 3}0.550{col 73}{space 4}-.2457687{col 86}{space 3} .1309365
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0511592{col 45}{space 2} .0964339{col 56}{space 1}   -0.53{col 65}{space 3}0.596{col 73}{space 4}-.2403638{col 86}{space 3} .1380453
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0552865{col 45}{space 2}  .037469{col 56}{space 1}    1.48{col 65}{space 3}0.140{col 73}{space 4}-.0182282{col 86}{space 3} .1288011
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0207947{col 45}{space 2} .0331877{col 56}{space 1}    0.63{col 65}{space 3}0.531{col 73}{space 4}  -.04432{col 86}{space 3} .0859093
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0127802{col 45}{space 2} .0381231{col 56}{space 1}   -0.34{col 65}{space 3}0.738{col 73}{space 4}-.0875782{col 86}{space 3} .0620178
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} -.017656{col 45}{space 2} .0341967{col 56}{space 1}   -0.52{col 65}{space 3}0.606{col 73}{space 4}-.0847503{col 86}{space 3} .0494383
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0416648{col 45}{space 2} .0365614{col 56}{space 1}   -1.14{col 65}{space 3}0.255{col 73}{space 4}-.1133988{col 86}{space 3} .0300691
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0534507{col 45}{space 2} .0466519{col 56}{space 1}   -1.15{col 65}{space 3}0.252{col 73}{space 4}-.1449823{col 86}{space 3} .0380809
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0238865{col 45}{space 2} .0359758{col 56}{space 1}   -0.66{col 65}{space 3}0.507{col 73}{space 4}-.0944715{col 86}{space 3} .0466986
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0593529{col 45}{space 2} .0537858{col 56}{space 1}    1.10{col 65}{space 3}0.270{col 73}{space 4}-.0461755{col 86}{space 3} .1648814
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0501138{col 45}{space 2} .0509462{col 56}{space 1}    0.98{col 65}{space 3}0.325{col 73}{space 4}-.0498433{col 86}{space 3} .1500709
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0673328{col 45}{space 2} .0345839{col 56}{space 1}   -1.95{col 65}{space 3}0.052{col 73}{space 4}-.1351868{col 86}{space 3} .0005213
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0377502{col 45}{space 2} .0364425{col 56}{space 1}   -1.04{col 65}{space 3}0.300{col 73}{space 4}-.1092509{col 86}{space 3} .0337505
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1262357{col 45}{space 2}  .059327{col 56}{space 1}    2.13{col 65}{space 3}0.034{col 73}{space 4} .0098354{col 86}{space 3}  .242636
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0879436{col 45}{space 2} .0552232{col 56}{space 1}    1.59{col 65}{space 3}0.112{col 73}{space 4}-.0204049{col 86}{space 3} .1962921
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2}-.0048501{col 45}{space 2} .0370258{col 56}{space 1}   -0.13{col 65}{space 3}0.896{col 73}{space 4}-.0774953{col 86}{space 3} .0677951
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0568389{col 45}{space 2} .0276208{col 56}{space 1}   -2.06{col 65}{space 3}0.040{col 73}{space 4}-.1110313{col 86}{space 3}-.0026466
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0240854{col 45}{space 2} .0438202{col 56}{space 1}   -0.55{col 65}{space 3}0.583{col 73}{space 4}-.1100613{col 86}{space 3} .0618905
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2} -.100017{col 45}{space 2}  .028573{col 56}{space 1}   -3.50{col 65}{space 3}0.000{col 73}{space 4}-.1560776{col 86}{space 3}-.0439564
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2} -.066312{col 45}{space 2} .0244437{col 56}{space 1}   -2.71{col 65}{space 3}0.007{col 73}{space 4}-.1142708{col 86}{space 3}-.0183532
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0193244{col 45}{space 2} .0558366{col 56}{space 1}   -0.35{col 65}{space 3}0.729{col 73}{space 4}-.1288765{col 86}{space 3} .0902276
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0640538{col 45}{space 2} .0364031{col 56}{space 1}   -1.76{col 65}{space 3}0.079{col 73}{space 4}-.1354772{col 86}{space 3} .0073696
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0844475{col 45}{space 2}  .025638{col 56}{space 1}   -3.29{col 65}{space 3}0.001{col 73}{space 4}-.1347496{col 86}{space 3}-.0341455
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .1045773{col 45}{space 2} .0811674{col 56}{space 1}    1.29{col 65}{space 3}0.198{col 73}{space 4}-.0546741{col 86}{space 3} .2638287
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} -.023349{col 45}{space 2} .0650073{col 56}{space 1}   -0.36{col 65}{space 3}0.720{col 73}{space 4}-.1508941{col 86}{space 3} .1041962
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}  .116929{col 45}{space 2} .1129541{col 56}{space 1}    1.04{col 65}{space 3}0.301{col 73}{space 4}-.1046884{col 86}{space 3} .3385463
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,620
                                                {txt}F(3, 1616)        =  {res}     1.51
                                                {txt}Prob > F          = {res}    0.2092
                                                {txt}R-squared         = {res}    0.0040
                                                {txt}Root MSE          =    {res} .30059

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}  -.00639{col 33}{space 2} .0156867{col 44}{space 1}   -0.41{col 53}{space 3}0.684{col 61}{space 4}-.0371584{col 74}{space 3} .0243784
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2} -.009666{col 33}{space 2} .0338044{col 44}{space 1}   -0.29{col 53}{space 3}0.775{col 61}{space 4} -.075971{col 74}{space 3} .0566391
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .0807453{col 33}{space 2} .0477886{col 44}{space 1}    1.69{col 53}{space 3}0.091{col 61}{space 4}-.0129888{col 74}{space 3} .1744795
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .0982736{col 33}{space 2} .0108616{col 44}{space 1}    9.05{col 53}{space 3}0.000{col 61}{space 4} .0769692{col 74}{space 3} .1195779
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,289
                                                {txt}F(44, 1244)       =  {res}     2.28
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0756
                                                {txt}Root MSE          =    {res} .28544

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}  -.01394{col 45}{space 2} .0181876{col 56}{space 1}   -0.77{col 65}{space 3}0.444{col 73}{space 4}-.0496218{col 86}{space 3} .0217418
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0389873{col 45}{space 2} .0305776{col 56}{space 1}   -1.28{col 65}{space 3}0.203{col 73}{space 4}-.0989767{col 86}{space 3} .0210021
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1154803{col 45}{space 2} .0490526{col 56}{space 1}    2.35{col 65}{space 3}0.019{col 73}{space 4} .0192454{col 86}{space 3} .2117153
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0273074{col 45}{space 2} .0165812{col 56}{space 1}    1.65{col 65}{space 3}0.100{col 73}{space 4}-.0052227{col 86}{space 3} .0598375
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2}-.0075836{col 45}{space 2} .0591686{col 56}{space 1}   -0.13{col 65}{space 3}0.898{col 73}{space 4} -.123665{col 86}{space 3} .1084977
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .081676{col 45}{space 2} .0421082{col 56}{space 1}    1.94{col 65}{space 3}0.053{col 73}{space 4}-.0009349{col 86}{space 3} .1642869
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0091515{col 45}{space 2} .0322182{col 56}{space 1}    0.28{col 65}{space 3}0.776{col 73}{space 4}-.0540565{col 86}{space 3} .0723594
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}  .010435{col 45}{space 2} .0296767{col 56}{space 1}    0.35{col 65}{space 3}0.725{col 73}{space 4} -.047787{col 86}{space 3}  .068657
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0054341{col 45}{space 2} .0296673{col 56}{space 1}    0.18{col 65}{space 3}0.855{col 73}{space 4}-.0527694{col 86}{space 3} .0636375
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0434636{col 45}{space 2} .0321507{col 56}{space 1}   -1.35{col 65}{space 3}0.177{col 73}{space 4}-.1065391{col 86}{space 3} .0196119
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0307719{col 45}{space 2} .0444567{col 56}{space 1}   -0.69{col 65}{space 3}0.489{col 73}{space 4}-.1179902{col 86}{space 3} .0564464
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0653574{col 45}{space 2}  .072776{col 56}{space 1}    0.90{col 65}{space 3}0.369{col 73}{space 4}-.0774198{col 86}{space 3} .2081346
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0789947{col 45}{space 2} .0483534{col 56}{space 1}   -1.63{col 65}{space 3}0.103{col 73}{space 4}-.1738579{col 86}{space 3} .0158684
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0976732{col 45}{space 2} .0442392{col 56}{space 1}   -2.21{col 65}{space 3}0.027{col 73}{space 4}-.1844649{col 86}{space 3}-.0108816
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0009528{col 45}{space 2} .0032565{col 56}{space 1}   -0.29{col 65}{space 3}0.770{col 73}{space 4}-.0073417{col 86}{space 3} .0054361
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000145{col 45}{space 2} .0000344{col 56}{space 1}    0.42{col 65}{space 3}0.672{col 73}{space 4}-.0000529{col 86}{space 3} .0000819
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2} -.085104{col 45}{space 2} .0962617{col 56}{space 1}   -0.88{col 65}{space 3}0.377{col 73}{space 4}-.2739571{col 86}{space 3} .1037492
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0467077{col 45}{space 2} .0983078{col 56}{space 1}   -0.48{col 65}{space 3}0.635{col 73}{space 4}-.2395751{col 86}{space 3} .1461598
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0949811{col 45}{space 2} .0986717{col 56}{space 1}   -0.96{col 65}{space 3}0.336{col 73}{space 4}-.2885624{col 86}{space 3} .0986003
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0888692{col 45}{space 2} .0981845{col 56}{space 1}   -0.91{col 65}{space 3}0.366{col 73}{space 4}-.2814947{col 86}{space 3} .1037563
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2} -.079201{col 45}{space 2} .0987006{col 56}{space 1}   -0.80{col 65}{space 3}0.422{col 73}{space 4}-.2728391{col 86}{space 3} .1144371
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0588685{col 45}{space 2} .0372667{col 56}{space 1}    1.58{col 65}{space 3}0.114{col 73}{space 4} -.014244{col 86}{space 3}  .131981
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0228202{col 45}{space 2} .0329606{col 56}{space 1}    0.69{col 65}{space 3}0.489{col 73}{space 4}-.0418443{col 86}{space 3} .0874846
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0070025{col 45}{space 2}  .038032{col 56}{space 1}    0.18{col 65}{space 3}0.854{col 73}{space 4}-.0676114{col 86}{space 3} .0816164
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0043407{col 45}{space 2} .0340661{col 56}{space 1}   -0.13{col 65}{space 3}0.899{col 73}{space 4} -.071174{col 86}{space 3} .0624926
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0415836{col 45}{space 2} .0379915{col 56}{space 1}   -1.09{col 65}{space 3}0.274{col 73}{space 4}-.1161182{col 86}{space 3}  .032951
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1021446{col 45}{space 2}  .042834{col 56}{space 1}   -2.38{col 65}{space 3}0.017{col 73}{space 4}-.1861794{col 86}{space 3}-.0181097
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0180744{col 45}{space 2} .0361689{col 56}{space 1}   -0.50{col 65}{space 3}0.617{col 73}{space 4}-.0890332{col 86}{space 3} .0528845
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0571927{col 45}{space 2} .0546599{col 56}{space 1}    1.05{col 65}{space 3}0.296{col 73}{space 4}-.0500431{col 86}{space 3} .1644285
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0566194{col 45}{space 2} .0522332{col 56}{space 1}    1.08{col 65}{space 3}0.279{col 73}{space 4}-.0458554{col 86}{space 3} .1590943
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0616406{col 45}{space 2} .0347176{col 56}{space 1}   -1.78{col 65}{space 3}0.076{col 73}{space 4} -.129752{col 86}{space 3} .0064709
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0358813{col 45}{space 2} .0367804{col 56}{space 1}   -0.98{col 65}{space 3}0.329{col 73}{space 4}-.1080397{col 86}{space 3} .0362772
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1274481{col 45}{space 2} .0597032{col 56}{space 1}    2.13{col 65}{space 3}0.033{col 73}{space 4} .0103179{col 86}{space 3} .2445782
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0833806{col 45}{space 2} .0554858{col 56}{space 1}    1.50{col 65}{space 3}0.133{col 73}{space 4}-.0254755{col 86}{space 3} .1922367
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0107687{col 45}{space 2} .0355197{col 56}{space 1}    0.30{col 65}{space 3}0.762{col 73}{space 4}-.0589165{col 86}{space 3}  .080454
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0532832{col 45}{space 2} .0276414{col 56}{space 1}   -1.93{col 65}{space 3}0.054{col 73}{space 4}-.1075121{col 86}{space 3} .0009456
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0213972{col 45}{space 2} .0434415{col 56}{space 1}   -0.49{col 65}{space 3}0.622{col 73}{space 4}-.1066239{col 86}{space 3} .0638295
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0937731{col 45}{space 2} .0289587{col 56}{space 1}   -3.24{col 65}{space 3}0.001{col 73}{space 4}-.1505864{col 86}{space 3}-.0369598
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0990361{col 45}{space 2}  .041773{col 56}{space 1}    2.37{col 65}{space 3}0.018{col 73}{space 4} .0170827{col 86}{space 3} .1809894
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0162995{col 45}{space 2} .0561382{col 56}{space 1}   -0.29{col 65}{space 3}0.772{col 73}{space 4}-.1264354{col 86}{space 3} .0938365
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0590737{col 45}{space 2} .0366631{col 56}{space 1}   -1.61{col 65}{space 3}0.107{col 73}{space 4} -.131002{col 86}{space 3} .0128547
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0926714{col 45}{space 2} .0265325{col 56}{space 1}   -3.49{col 65}{space 3}0.000{col 73}{space 4}-.1447249{col 86}{space 3}-.0406179
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}  .091289{col 45}{space 2} .0812307{col 56}{space 1}    1.12{col 65}{space 3}0.261{col 73}{space 4}-.0680753{col 86}{space 3} .2506532
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0314303{col 45}{space 2} .0645777{col 56}{space 1}   -0.49{col 65}{space 3}0.627{col 73}{space 4}-.1581235{col 86}{space 3}  .095263
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1518915{col 45}{space 2} .1156009{col 56}{space 1}    1.31{col 65}{space 3}0.189{col 73}{space 4}-.0749027{col 86}{space 3} .3786857
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,773
                                                {txt}F(3, 1769)        =  {res}     2.35
                                                {txt}Prob > F          = {res}    0.0708
                                                {txt}R-squared         = {res}    0.0057
                                                {txt}Root MSE          =    {res} .30735

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0048955{col 33}{space 2} .0156202{col 44}{space 1}   -0.31{col 53}{space 3}0.754{col 61}{space 4}-.0355315{col 74}{space 3} .0257405
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0259009{col 33}{space 2} .0268877{col 44}{space 1}   -0.96{col 53}{space 3}0.336{col 61}{space 4}-.0786358{col 74}{space 3} .0268341
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1133558{col 33}{space 2} .0451541{col 44}{space 1}    2.51{col 53}{space 3}0.012{col 61}{space 4} .0247948{col 74}{space 3} .2019169
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1034871{col 33}{space 2} .0102273{col 44}{space 1}   10.12{col 53}{space 3}0.000{col 61}{space 4} .0834282{col 74}{space 3} .1235459
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,321
                                                {txt}F(44, 1276)       =  {res}     2.35
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0798
                                                {txt}Root MSE          =    {res} .27944

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0241919{col 45}{space 2} .0176312{col 56}{space 1}   -1.37{col 65}{space 3}0.170{col 73}{space 4}-.0587811{col 86}{space 3} .0103974
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0405929{col 45}{space 2} .0298667{col 56}{space 1}   -1.36{col 65}{space 3}0.174{col 73}{space 4}-.0991861{col 86}{space 3} .0180003
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1123795{col 45}{space 2} .0461255{col 56}{space 1}    2.44{col 65}{space 3}0.015{col 73}{space 4} .0218894{col 86}{space 3} .2028696
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0293014{col 45}{space 2} .0158731{col 56}{space 1}    1.85{col 65}{space 3}0.065{col 73}{space 4}-.0018388{col 86}{space 3} .0604417
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0238356{col 45}{space 2} .0637444{col 56}{space 1}    0.37{col 65}{space 3}0.709{col 73}{space 4}-.1012197{col 86}{space 3} .1488909
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2}  .085634{col 45}{space 2} .0415102{col 56}{space 1}    2.06{col 65}{space 3}0.039{col 73}{space 4} .0041983{col 86}{space 3} .1670697
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}  .000789{col 45}{space 2} .0301362{col 56}{space 1}    0.03{col 65}{space 3}0.979{col 73}{space 4}-.0583329{col 86}{space 3} .0599109
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0115994{col 45}{space 2} .0287844{col 56}{space 1}    0.40{col 65}{space 3}0.687{col 73}{space 4}-.0448707{col 86}{space 3} .0680694
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2}  .005384{col 45}{space 2}  .028424{col 56}{space 1}    0.19{col 65}{space 3}0.850{col 73}{space 4}-.0503789{col 86}{space 3}  .061147
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0466234{col 45}{space 2} .0296571{col 56}{space 1}   -1.57{col 65}{space 3}0.116{col 73}{space 4}-.1048054{col 86}{space 3} .0115587
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0283647{col 45}{space 2} .0443133{col 56}{space 1}   -0.64{col 65}{space 3}0.522{col 73}{space 4}-.1152996{col 86}{space 3} .0585701
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0693089{col 45}{space 2} .0720478{col 56}{space 1}    0.96{col 65}{space 3}0.336{col 73}{space 4}-.0720362{col 86}{space 3} .2106541
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}  -.08659{col 45}{space 2} .0462554{col 56}{space 1}   -1.87{col 65}{space 3}0.061{col 73}{space 4}-.1773349{col 86}{space 3} .0041549
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0768851{col 45}{space 2} .0431292{col 56}{space 1}   -1.78{col 65}{space 3}0.075{col 73}{space 4}-.1614969{col 86}{space 3} .0077268
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0012862{col 45}{space 2} .0031814{col 56}{space 1}   -0.40{col 65}{space 3}0.686{col 73}{space 4}-.0075276{col 86}{space 3} .0049553
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000179{col 45}{space 2} .0000337{col 56}{space 1}    0.53{col 65}{space 3}0.595{col 73}{space 4}-.0000481{col 86}{space 3}  .000084
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0942125{col 45}{space 2} .0956712{col 56}{space 1}   -0.98{col 65}{space 3}0.325{col 73}{space 4}-.2819026{col 86}{space 3} .0934776
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0515124{col 45}{space 2} .0986148{col 56}{space 1}   -0.52{col 65}{space 3}0.602{col 73}{space 4}-.2449774{col 86}{space 3} .1419526
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0944746{col 45}{space 2} .0989793{col 56}{space 1}   -0.95{col 65}{space 3}0.340{col 73}{space 4}-.2886546{col 86}{space 3} .0997053
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0867195{col 45}{space 2}  .098514{col 56}{space 1}   -0.88{col 65}{space 3}0.379{col 73}{space 4}-.2799867{col 86}{space 3} .1065476
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0760783{col 45}{space 2} .0991532{col 56}{space 1}   -0.77{col 65}{space 3}0.443{col 73}{space 4}-.2705994{col 86}{space 3} .1184429
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .044079{col 45}{space 2} .0387434{col 56}{space 1}    1.14{col 65}{space 3}0.255{col 73}{space 4}-.0319288{col 86}{space 3} .1200867
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0119326{col 45}{space 2} .0346446{col 56}{space 1}    0.34{col 65}{space 3}0.731{col 73}{space 4} -.056034{col 86}{space 3} .0798992
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2}-.0037009{col 45}{space 2} .0389332{col 56}{space 1}   -0.10{col 65}{space 3}0.924{col 73}{space 4} -.080081{col 86}{space 3} .0726792
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0148235{col 45}{space 2} .0356598{col 56}{space 1}   -0.42{col 65}{space 3}0.678{col 73}{space 4}-.0847818{col 86}{space 3} .0551347
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0501942{col 45}{space 2} .0373556{col 56}{space 1}   -1.34{col 65}{space 3}0.179{col 73}{space 4}-.1234794{col 86}{space 3} .0230911
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1131607{col 45}{space 2} .0437563{col 56}{space 1}   -2.59{col 65}{space 3}0.010{col 73}{space 4}-.1990028{col 86}{space 3}-.0273186
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0230308{col 45}{space 2} .0358186{col 56}{space 1}   -0.64{col 65}{space 3}0.520{col 73}{space 4}-.0933006{col 86}{space 3}  .047239
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0547412{col 45}{space 2} .0542351{col 56}{space 1}    1.01{col 65}{space 3}0.313{col 73}{space 4}-.0516586{col 86}{space 3} .1611409
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0502345{col 45}{space 2} .0514238{col 56}{space 1}    0.98{col 65}{space 3}0.329{col 73}{space 4}-.0506499{col 86}{space 3} .1511189
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2} -.059533{col 45}{space 2}  .034299{col 56}{space 1}   -1.74{col 65}{space 3}0.083{col 73}{space 4}-.1268215{col 86}{space 3} .0077556
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0369655{col 45}{space 2} .0366606{col 56}{space 1}   -1.01{col 65}{space 3}0.313{col 73}{space 4}-.1088872{col 86}{space 3} .0349563
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1257387{col 45}{space 2} .0597891{col 56}{space 1}    2.10{col 65}{space 3}0.036{col 73}{space 4}  .008443{col 86}{space 3} .2430344
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0844092{col 45}{space 2} .0554483{col 56}{space 1}    1.52{col 65}{space 3}0.128{col 73}{space 4}-.0243707{col 86}{space 3} .1931891
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0046277{col 45}{space 2} .0350957{col 56}{space 1}    0.13{col 65}{space 3}0.895{col 73}{space 4}-.0642239{col 86}{space 3} .0734794
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0561164{col 45}{space 2} .0275656{col 56}{space 1}   -2.04{col 65}{space 3}0.042{col 73}{space 4}-.1101953{col 86}{space 3}-.0020375
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2} -.021425{col 45}{space 2} .0433419{col 56}{space 1}   -0.49{col 65}{space 3}0.621{col 73}{space 4}-.1064542{col 86}{space 3} .0636043
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0941525{col 45}{space 2} .0286724{col 56}{space 1}   -3.28{col 65}{space 3}0.001{col 73}{space 4}-.1504028{col 86}{space 3}-.0379023
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0923172{col 45}{space 2} .0414563{col 56}{space 1}    2.23{col 65}{space 3}0.026{col 73}{space 4} .0109871{col 86}{space 3} .1736472
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0635175{col 45}{space 2} .0247194{col 56}{space 1}   -2.57{col 65}{space 3}0.010{col 73}{space 4}-.1120126{col 86}{space 3}-.0150224
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0621982{col 45}{space 2} .0363017{col 56}{space 1}   -1.71{col 65}{space 3}0.087{col 73}{space 4}-.1334158{col 86}{space 3} .0090193
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2} -.095166{col 45}{space 2} .0257793{col 56}{space 1}   -3.69{col 65}{space 3}0.000{col 73}{space 4}-.1457404{col 86}{space 3}-.0445916
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0929423{col 45}{space 2} .0812834{col 56}{space 1}    1.14{col 65}{space 3}0.253{col 73}{space 4}-.0665215{col 86}{space 3} .2524062
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0312354{col 45}{space 2}   .06488{col 56}{space 1}   -0.48{col 65}{space 3}0.630{col 73}{space 4}-.1585187{col 86}{space 3} .0960478
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1769431{col 45}{space 2} .1132696{col 56}{space 1}    1.56{col 65}{space 3}0.119{col 73}{space 4} -.045272{col 86}{space 3} .3991581
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,806
                                                {txt}F(3, 1802)        =  {res}     2.21
                                                {txt}Prob > F          = {res}    0.0850
                                                {txt}R-squared         = {res}    0.0052
                                                {txt}Root MSE          =    {res} .30132

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0102145{col 33}{space 2} .0150949{col 44}{space 1}   -0.68{col 53}{space 3}0.499{col 61}{space 4}-.0398198{col 74}{space 3} .0193908
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0242005{col 33}{space 2}  .026657{col 44}{space 1}   -0.91{col 53}{space 3}0.364{col 61}{space 4}-.0764823{col 74}{space 3} .0280813
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1059533{col 33}{space 2}  .043198{col 44}{space 1}    2.45{col 53}{space 3}0.014{col 61}{space 4} .0212298{col 74}{space 3} .1906768
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1011236{col 33}{space 2} .0101173{col 44}{space 1}   10.00{col 53}{space 3}0.000{col 61}{space 4} .0812808{col 74}{space 3} .1209664
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,317
                                                {txt}F(44, 1272)       =  {res}     2.35
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0773
                                                {txt}Root MSE          =    {res} .28233

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0136829{col 45}{space 2} .0179899{col 56}{space 1}   -0.76{col 65}{space 3}0.447{col 73}{space 4}-.0489761{col 86}{space 3} .0216103
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0385222{col 45}{space 2} .0296884{col 56}{space 1}   -1.30{col 65}{space 3}0.195{col 73}{space 4}-.0967659{col 86}{space 3} .0197214
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1065544{col 45}{space 2} .0463203{col 56}{space 1}    2.30{col 65}{space 3}0.022{col 73}{space 4} .0156819{col 86}{space 3} .1974269
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0319307{col 45}{space 2} .0162009{col 56}{space 1}    1.97{col 65}{space 3}0.049{col 73}{space 4} .0001474{col 86}{space 3} .0637141
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0243559{col 45}{space 2} .0637828{col 56}{space 1}    0.38{col 65}{space 3}0.703{col 73}{space 4}-.1007752{col 86}{space 3} .1494871
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0848633{col 45}{space 2} .0418114{col 56}{space 1}    2.03{col 65}{space 3}0.043{col 73}{space 4} .0028364{col 86}{space 3} .1668902
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0066061{col 45}{space 2} .0311115{col 56}{space 1}    0.21{col 65}{space 3}0.832{col 73}{space 4}-.0544294{col 86}{space 3} .0676415
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2}  .012345{col 45}{space 2} .0288762{col 56}{space 1}    0.43{col 65}{space 3}0.669{col 73}{space 4}-.0443052{col 86}{space 3} .0689952
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0085907{col 45}{space 2} .0288669{col 56}{space 1}    0.30{col 65}{space 3}0.766{col 73}{space 4}-.0480413{col 86}{space 3} .0652226
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0377159{col 45}{space 2} .0312149{col 56}{space 1}   -1.21{col 65}{space 3}0.227{col 73}{space 4}-.0989543{col 86}{space 3} .0235225
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0259643{col 45}{space 2} .0437266{col 56}{space 1}   -0.59{col 65}{space 3}0.553{col 73}{space 4}-.1117485{col 86}{space 3} .0598199
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0630125{col 45}{space 2} .0676077{col 56}{space 1}    0.93{col 65}{space 3}0.351{col 73}{space 4}-.0696224{col 86}{space 3} .1956474
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0766397{col 45}{space 2} .0481566{col 56}{space 1}   -1.59{col 65}{space 3}0.112{col 73}{space 4}-.1711148{col 86}{space 3} .0178353
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0768351{col 45}{space 2} .0419888{col 56}{space 1}   -1.83{col 65}{space 3}0.067{col 73}{space 4}  -.15921{col 86}{space 3} .0055398
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0014807{col 45}{space 2} .0032653{col 56}{space 1}   -0.45{col 65}{space 3}0.650{col 73}{space 4}-.0078867{col 86}{space 3} .0049252
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000203{col 45}{space 2} .0000347{col 56}{space 1}    0.59{col 65}{space 3}0.558{col 73}{space 4}-.0000478{col 86}{space 3} .0000884
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0875883{col 45}{space 2}  .091861{col 56}{space 1}   -0.95{col 65}{space 3}0.341{col 73}{space 4}-.2678041{col 86}{space 3} .0926274
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0404194{col 45}{space 2} .0948393{col 56}{space 1}   -0.43{col 65}{space 3}0.670{col 73}{space 4}-.2264781{col 86}{space 3} .1456392
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0892989{col 45}{space 2} .0950481{col 56}{space 1}   -0.94{col 65}{space 3}0.348{col 73}{space 4}-.2757672{col 86}{space 3} .0971694
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0770696{col 45}{space 2} .0945011{col 56}{space 1}   -0.82{col 65}{space 3}0.415{col 73}{space 4}-.2624647{col 86}{space 3} .1083256
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0734202{col 45}{space 2} .0951257{col 56}{space 1}   -0.77{col 65}{space 3}0.440{col 73}{space 4}-.2600408{col 86}{space 3} .1132003
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0681072{col 45}{space 2} .0360862{col 56}{space 1}    1.89{col 65}{space 3}0.059{col 73}{space 4}-.0026879{col 86}{space 3} .1389022
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0318537{col 45}{space 2} .0312282{col 56}{space 1}    1.02{col 65}{space 3}0.308{col 73}{space 4}-.0294108{col 86}{space 3} .0931182
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0189307{col 45}{space 2} .0366298{col 56}{space 1}    0.52{col 65}{space 3}0.605{col 73}{space 4}-.0529309{col 86}{space 3} .0907922
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2} .0049474{col 45}{space 2} .0321127{col 56}{space 1}    0.15{col 65}{space 3}0.878{col 73}{space 4}-.0580522{col 86}{space 3}  .067947
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0272385{col 45}{space 2} .0348567{col 56}{space 1}   -0.78{col 65}{space 3}0.435{col 73}{space 4}-.0956213{col 86}{space 3} .0411444
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0928387{col 45}{space 2} .0414721{col 56}{space 1}   -2.24{col 65}{space 3}0.025{col 73}{space 4}   -.1742{col 86}{space 3}-.0114774
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}  -.01913{col 45}{space 2} .0356918{col 56}{space 1}   -0.54{col 65}{space 3}0.592{col 73}{space 4}-.0891513{col 86}{space 3} .0508913
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0569781{col 45}{space 2} .0542541{col 56}{space 1}    1.05{col 65}{space 3}0.294{col 73}{space 4}-.0494593{col 86}{space 3} .1634154
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0531432{col 45}{space 2} .0515719{col 56}{space 1}    1.03{col 65}{space 3}0.303{col 73}{space 4}-.0480322{col 86}{space 3} .1543185
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0633596{col 45}{space 2} .0343761{col 56}{space 1}   -1.84{col 65}{space 3}0.066{col 73}{space 4}-.1307998{col 86}{space 3} .0040805
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2} -.033827{col 45}{space 2}  .036483{col 56}{space 1}   -0.93{col 65}{space 3}0.354{col 73}{space 4}-.1054004{col 86}{space 3} .0377465
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1255777{col 45}{space 2} .0597064{col 56}{space 1}    2.10{col 65}{space 3}0.036{col 73}{space 4} .0084438{col 86}{space 3} .2427116
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0866265{col 45}{space 2} .0555378{col 56}{space 1}    1.56{col 65}{space 3}0.119{col 73}{space 4}-.0223292{col 86}{space 3} .1955822
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0103515{col 45}{space 2} .0352113{col 56}{space 1}    0.29{col 65}{space 3}0.769{col 73}{space 4} -.058727{col 86}{space 3}   .07943
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0548705{col 45}{space 2} .0276341{col 56}{space 1}   -1.99{col 65}{space 3}0.047{col 73}{space 4}-.1090839{col 86}{space 3} -.000657
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0189317{col 45}{space 2} .0431784{col 56}{space 1}   -0.44{col 65}{space 3}0.661{col 73}{space 4}-.1036404{col 86}{space 3}  .065777
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0935025{col 45}{space 2} .0285864{col 56}{space 1}   -3.27{col 65}{space 3}0.001{col 73}{space 4}-.1495841{col 86}{space 3}-.0374208
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0976881{col 45}{space 2} .0415757{col 56}{space 1}    2.35{col 65}{space 3}0.019{col 73}{space 4} .0161236{col 86}{space 3} .1792525
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0645237{col 45}{space 2} .0247189{col 56}{space 1}   -2.61{col 65}{space 3}0.009{col 73}{space 4}-.1130179{col 86}{space 3}-.0160294
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0144509{col 45}{space 2} .0559588{col 56}{space 1}   -0.26{col 65}{space 3}0.796{col 73}{space 4}-.1242326{col 86}{space 3} .0953309
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}  -.09053{col 45}{space 2} .0260384{col 56}{space 1}   -3.48{col 65}{space 3}0.001{col 73}{space 4} -.141613{col 86}{space 3}-.0394471
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0888838{col 45}{space 2} .0812328{col 56}{space 1}    1.09{col 65}{space 3}0.274{col 73}{space 4}-.0704813{col 86}{space 3} .2482488
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0332454{col 45}{space 2} .0649121{col 56}{space 1}   -0.51{col 65}{space 3}0.609{col 73}{space 4}-.1605919{col 86}{space 3} .0941011
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1426025{col 45}{space 2} .1113406{col 56}{space 1}    1.28{col 65}{space 3}0.201{col 73}{space 4}-.0758289{col 86}{space 3} .3610338
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,789
                                                {txt}F(3, 1785)        =  {res}     2.11
                                                {txt}Prob > F          = {res}    0.0972
                                                {txt}R-squared         = {res}    0.0048
                                                {txt}Root MSE          =    {res} .30555

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0071965{col 33}{space 2} .0154669{col 44}{space 1}   -0.47{col 53}{space 3}0.642{col 61}{space 4}-.0375316{col 74}{space 3} .0231387
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0272555{col 33}{space 2} .0265373{col 44}{space 1}   -1.03{col 53}{space 3}0.305{col 61}{space 4}-.0793029{col 74}{space 3} .0247918
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1048383{col 33}{space 2} .0433708{col 44}{space 1}    2.42{col 53}{space 3}0.016{col 61}{space 4} .0197754{col 74}{space 3} .1899013
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1035267{col 33}{space 2} .0102869{col 44}{space 1}   10.06{col 53}{space 3}0.000{col 61}{space 4}  .083351{col 74}{space 3} .1237025
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,331
                                                {txt}F(44, 1286)       =  {res}     2.09
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.0756
                                                {txt}Root MSE          =    {res} .28224

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0158507{col 45}{space 2} .0177876{col 56}{space 1}   -0.89{col 65}{space 3}0.373{col 73}{space 4}-.0507465{col 86}{space 3} .0190451
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0419932{col 45}{space 2} .0307172{col 56}{space 1}   -1.37{col 65}{space 3}0.172{col 73}{space 4}-.1022546{col 86}{space 3} .0182682
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1110319{col 45}{space 2} .0476835{col 56}{space 1}    2.33{col 65}{space 3}0.020{col 73}{space 4} .0174859{col 86}{space 3} .2045779
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0293699{col 45}{space 2}   .01614{col 56}{space 1}    1.82{col 65}{space 3}0.069{col 73}{space 4}-.0022936{col 86}{space 3} .0610335
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0256055{col 45}{space 2}  .063892{col 56}{space 1}    0.40{col 65}{space 3}0.689{col 73}{space 4}-.0997385{col 86}{space 3} .1509495
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0830768{col 45}{space 2} .0415565{col 56}{space 1}    2.00{col 65}{space 3}0.046{col 73}{space 4} .0015508{col 86}{space 3} .1646029
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0108512{col 45}{space 2} .0308312{col 56}{space 1}    0.35{col 65}{space 3}0.725{col 73}{space 4}-.0496337{col 86}{space 3} .0713361
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0123564{col 45}{space 2}  .028762{col 56}{space 1}    0.43{col 65}{space 3}0.668{col 73}{space 4}-.0440691{col 86}{space 3} .0687819
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0072951{col 45}{space 2} .0284592{col 56}{space 1}    0.26{col 65}{space 3}0.798{col 73}{space 4}-.0485365{col 86}{space 3} .0631267
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0364006{col 45}{space 2} .0309322{col 56}{space 1}   -1.18{col 65}{space 3}0.239{col 73}{space 4}-.0970837{col 86}{space 3} .0242826
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0242171{col 45}{space 2}  .043258{col 56}{space 1}   -0.56{col 65}{space 3}0.576{col 73}{space 4}-.1090811{col 86}{space 3} .0606469
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0683137{col 45}{space 2} .0725001{col 56}{space 1}    0.94{col 65}{space 3}0.346{col 73}{space 4}-.0739177{col 86}{space 3}  .210545
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2} -.074544{col 45}{space 2} .0482296{col 56}{space 1}   -1.55{col 65}{space 3}0.122{col 73}{space 4}-.1691613{col 86}{space 3} .0200733
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0729828{col 45}{space 2} .0423196{col 56}{space 1}   -1.72{col 65}{space 3}0.085{col 73}{space 4}-.1560059{col 86}{space 3} .0100403
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0012963{col 45}{space 2} .0031812{col 56}{space 1}   -0.41{col 65}{space 3}0.684{col 73}{space 4}-.0075372{col 86}{space 3} .0049446
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000178{col 45}{space 2} .0000337{col 56}{space 1}    0.53{col 65}{space 3}0.598{col 73}{space 4}-.0000484{col 86}{space 3}  .000084
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0804336{col 45}{space 2} .0923963{col 56}{space 1}   -0.87{col 65}{space 3}0.384{col 73}{space 4}-.2616976{col 86}{space 3} .1008304
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0422664{col 45}{space 2} .0949042{col 56}{space 1}   -0.45{col 65}{space 3}0.656{col 73}{space 4}-.2284505{col 86}{space 3} .1439176
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0896572{col 45}{space 2} .0952477{col 56}{space 1}   -0.94{col 65}{space 3}0.347{col 73}{space 4}-.2765152{col 86}{space 3} .0972007
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}  -.08011{col 45}{space 2} .0946597{col 56}{space 1}   -0.85{col 65}{space 3}0.398{col 73}{space 4}-.2658144{col 86}{space 3} .1055943
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0752908{col 45}{space 2} .0953057{col 56}{space 1}   -0.79{col 65}{space 3}0.430{col 73}{space 4}-.2622624{col 86}{space 3} .1116809
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2}  .054169{col 45}{space 2} .0380386{col 56}{space 1}    1.42{col 65}{space 3}0.155{col 73}{space 4}-.0204556{col 86}{space 3} .1287935
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0189495{col 45}{space 2} .0336408{col 56}{space 1}    0.56{col 65}{space 3}0.573{col 73}{space 4}-.0470474{col 86}{space 3} .0849463
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0047217{col 45}{space 2} .0384548{col 56}{space 1}    0.12{col 65}{space 3}0.902{col 73}{space 4}-.0707193{col 86}{space 3} .0801626
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0093787{col 45}{space 2} .0353685{col 56}{space 1}   -0.27{col 65}{space 3}0.791{col 73}{space 4} -.078765{col 86}{space 3} .0600075
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0398388{col 45}{space 2} .0369843{col 56}{space 1}   -1.08{col 65}{space 3}0.282{col 73}{space 4} -.112395{col 86}{space 3} .0327174
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1055114{col 45}{space 2} .0436017{col 56}{space 1}   -2.42{col 65}{space 3}0.016{col 73}{space 4}-.1910496{col 86}{space 3}-.0199732
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0226207{col 45}{space 2} .0358264{col 56}{space 1}   -0.63{col 65}{space 3}0.528{col 73}{space 4}-.0929052{col 86}{space 3} .0476639
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0569293{col 45}{space 2} .0542518{col 56}{space 1}    1.05{col 65}{space 3}0.294{col 73}{space 4}-.0495024{col 86}{space 3}  .163361
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0524283{col 45}{space 2} .0516884{col 56}{space 1}    1.01{col 65}{space 3}0.311{col 73}{space 4}-.0489746{col 86}{space 3} .1538313
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0621642{col 45}{space 2} .0344139{col 56}{space 1}   -1.81{col 65}{space 3}0.071{col 73}{space 4}-.1296777{col 86}{space 3} .0053494
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0356353{col 45}{space 2} .0365829{col 56}{space 1}   -0.97{col 65}{space 3}0.330{col 73}{space 4}-.1074039{col 86}{space 3} .0361334
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1263639{col 45}{space 2} .0597019{col 56}{space 1}    2.12{col 65}{space 3}0.034{col 73}{space 4}   .00924{col 86}{space 3} .2434877
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0844784{col 45}{space 2} .0553261{col 56}{space 1}    1.53{col 65}{space 3}0.127{col 73}{space 4}-.0240609{col 86}{space 3} .1930177
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0090581{col 45}{space 2}  .035215{col 56}{space 1}    0.26{col 65}{space 3}0.797{col 73}{space 4} -.060027{col 86}{space 3} .0781433
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0549705{col 45}{space 2} .0276264{col 56}{space 1}   -1.99{col 65}{space 3}0.047{col 73}{space 4}-.1091682{col 86}{space 3}-.0007727
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0209093{col 45}{space 2} .0433316{col 56}{space 1}   -0.48{col 65}{space 3}0.630{col 73}{space 4}-.1059176{col 86}{space 3}  .064099
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0932248{col 45}{space 2} .0285608{col 56}{space 1}   -3.26{col 65}{space 3}0.001{col 73}{space 4}-.1492557{col 86}{space 3}-.0371938
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0979627{col 45}{space 2} .0415287{col 56}{space 1}    2.36{col 65}{space 3}0.018{col 73}{space 4} .0164913{col 86}{space 3} .1794341
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0644555{col 45}{space 2} .0247309{col 56}{space 1}   -2.61{col 65}{space 3}0.009{col 73}{space 4}-.1129728{col 86}{space 3}-.0159382
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0162504{col 45}{space 2} .0559122{col 56}{space 1}   -0.29{col 65}{space 3}0.771{col 73}{space 4}-.1259395{col 86}{space 3} .0934386
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0598328{col 45}{space 2}  .036266{col 56}{space 1}   -1.65{col 65}{space 3}0.099{col 73}{space 4}-.1309799{col 86}{space 3} .0113143
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0921996{col 45}{space 2} .0811716{col 56}{space 1}    1.14{col 65}{space 3}0.256{col 73}{space 4}-.0670437{col 86}{space 3}  .251443
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0326992{col 45}{space 2} .0645443{col 56}{space 1}   -0.51{col 65}{space 3}0.613{col 73}{space 4}-.1593229{col 86}{space 3} .0939246
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1561031{col 45}{space 2} .1115148{col 56}{space 1}    1.40{col 65}{space 3}0.162{col 73}{space 4}-.0626679{col 86}{space 3} .3748741
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,787
                                                {txt}F(3, 1783)        =  {res}     1.81
                                                {txt}Prob > F          = {res}    0.1424
                                                {txt}R-squared         = {res}    0.0042
                                                {txt}Root MSE          =    {res} .30361

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2} -.009235{col 33}{space 2} .0152853{col 44}{space 1}   -0.60{col 53}{space 3}0.546{col 61}{space 4}-.0392139{col 74}{space 3} .0207439
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0217122{col 33}{space 2} .0278571{col 44}{space 1}   -0.78{col 53}{space 3}0.436{col 61}{space 4}-.0763482{col 74}{space 3} .0329238
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .0986966{col 33}{space 2} .0447818{col 44}{space 1}    2.20{col 53}{space 3}0.028{col 61}{space 4} .0108662{col 74}{space 3} .1865269
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1027933{col 33}{space 2} .0101626{col 44}{space 1}   10.11{col 53}{space 3}0.000{col 61}{space 4} .0828615{col 74}{space 3} .1227251
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,330
                                                {txt}F(44, 1285)       =  {res}     2.27
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0750
                                                {txt}Root MSE          =    {res} .27716

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0200637{col 45}{space 2} .0174805{col 56}{space 1}   -1.15{col 65}{space 3}0.251{col 73}{space 4}-.0543572{col 86}{space 3} .0142297
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}  -.03919{col 45}{space 2} .0296491{col 56}{space 1}   -1.32{col 65}{space 3}0.186{col 73}{space 4} -.097356{col 86}{space 3}  .018976
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1038637{col 45}{space 2} .0461142{col 56}{space 1}    2.25{col 65}{space 3}0.024{col 73}{space 4} .0133963{col 86}{space 3}  .194331
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0263639{col 45}{space 2} .0158214{col 56}{space 1}    1.67{col 65}{space 3}0.096{col 73}{space 4}-.0046748{col 86}{space 3} .0574026
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0306859{col 45}{space 2} .0634996{col 56}{space 1}    0.48{col 65}{space 3}0.629{col 73}{space 4}-.0938883{col 86}{space 3} .1552601
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0792721{col 45}{space 2} .0402076{col 56}{space 1}    1.97{col 65}{space 3}0.049{col 73}{space 4} .0003923{col 86}{space 3} .1581518
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2} .0139165{col 45}{space 2}  .030381{col 56}{space 1}    0.46{col 65}{space 3}0.647{col 73}{space 4}-.0456853{col 86}{space 3} .0735183
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0151413{col 45}{space 2} .0280232{col 56}{space 1}    0.54{col 65}{space 3}0.589{col 73}{space 4}-.0398349{col 86}{space 3} .0701175
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0159882{col 45}{space 2} .0281088{col 56}{space 1}    0.57{col 65}{space 3}0.570{col 73}{space 4}-.0391559{col 86}{space 3} .0711322
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0311289{col 45}{space 2} .0303898{col 56}{space 1}   -1.02{col 65}{space 3}0.306{col 73}{space 4}-.0907481{col 86}{space 3} .0284902
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0220178{col 45}{space 2} .0425386{col 56}{space 1}   -0.52{col 65}{space 3}0.605{col 73}{space 4}-.1054705{col 86}{space 3} .0614349
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0663316{col 45}{space 2} .0672342{col 56}{space 1}    0.99{col 65}{space 3}0.324{col 73}{space 4}-.0655692{col 86}{space 3} .1982323
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0747295{col 45}{space 2} .0459884{col 56}{space 1}   -1.62{col 65}{space 3}0.104{col 73}{space 4}-.1649501{col 86}{space 3} .0154911
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0731641{col 45}{space 2} .0422096{col 56}{space 1}   -1.73{col 65}{space 3}0.083{col 73}{space 4}-.1559713{col 86}{space 3} .0096431
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0018231{col 45}{space 2} .0031635{col 56}{space 1}   -0.58{col 65}{space 3}0.565{col 73}{space 4}-.0080292{col 86}{space 3} .0043831
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000233{col 45}{space 2} .0000338{col 56}{space 1}    0.69{col 65}{space 3}0.490{col 73}{space 4}-.0000429{col 86}{space 3} .0000895
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0788708{col 45}{space 2} .0922264{col 56}{space 1}   -0.86{col 65}{space 3}0.393{col 73}{space 4}-.2598017{col 86}{space 3} .1020602
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0443472{col 45}{space 2} .0946121{col 56}{space 1}   -0.47{col 65}{space 3}0.639{col 73}{space 4}-.2299584{col 86}{space 3} .1412639
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0935524{col 45}{space 2} .0948455{col 56}{space 1}   -0.99{col 65}{space 3}0.324{col 73}{space 4}-.2796213{col 86}{space 3} .0925166
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0749473{col 45}{space 2} .0944703{col 56}{space 1}   -0.79{col 65}{space 3}0.428{col 73}{space 4}-.2602802{col 86}{space 3} .1103856
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0723535{col 45}{space 2} .0951033{col 56}{space 1}   -0.76{col 65}{space 3}0.447{col 73}{space 4}-.2589283{col 86}{space 3} .1142213
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0541617{col 45}{space 2} .0370265{col 56}{space 1}    1.46{col 65}{space 3}0.144{col 73}{space 4}-.0184773{col 86}{space 3} .1268007
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0181361{col 45}{space 2} .0326786{col 56}{space 1}    0.55{col 65}{space 3}0.579{col 73}{space 4}-.0459732{col 86}{space 3} .0822454
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0041038{col 45}{space 2} .0377105{col 56}{space 1}    0.11{col 65}{space 3}0.913{col 73}{space 4} -.069877{col 86}{space 3} .0780847
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0097107{col 45}{space 2} .0338073{col 56}{space 1}   -0.29{col 65}{space 3}0.774{col 73}{space 4}-.0760343{col 86}{space 3}  .056613
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0419012{col 45}{space 2} .0360741{col 56}{space 1}   -1.16{col 65}{space 3}0.246{col 73}{space 4}-.1126717{col 86}{space 3} .0288693
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1083422{col 45}{space 2} .0427297{col 56}{space 1}   -2.54{col 65}{space 3}0.011{col 73}{space 4}-.1921699{col 86}{space 3}-.0245145
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2} -.024417{col 45}{space 2} .0357134{col 56}{space 1}   -0.68{col 65}{space 3}0.494{col 73}{space 4}  -.09448{col 86}{space 3}  .045646
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0539992{col 45}{space 2} .0544539{col 56}{space 1}    0.99{col 65}{space 3}0.322{col 73}{space 4}-.0528291{col 86}{space 3} .1608274
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0500671{col 45}{space 2} .0516579{col 56}{space 1}    0.97{col 65}{space 3}0.333{col 73}{space 4} -.051276{col 86}{space 3} .1514102
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0611164{col 45}{space 2} .0342176{col 56}{space 1}   -1.79{col 65}{space 3}0.074{col 73}{space 4}-.1282449{col 86}{space 3}  .006012
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0380791{col 45}{space 2} .0365634{col 56}{space 1}   -1.04{col 65}{space 3}0.298{col 73}{space 4}-.1098095{col 86}{space 3} .0336514
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1248995{col 45}{space 2} .0598021{col 56}{space 1}    2.09{col 65}{space 3}0.037{col 73}{space 4} .0075789{col 86}{space 3}   .24222
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2} .0827856{col 45}{space 2} .0554232{col 56}{space 1}    1.49{col 65}{space 3}0.135{col 73}{space 4}-.0259443{col 86}{space 3} .1915155
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0051392{col 45}{space 2} .0350535{col 56}{space 1}    0.15{col 65}{space 3}0.883{col 73}{space 4}-.0636292{col 86}{space 3} .0739076
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0559411{col 45}{space 2} .0275256{col 56}{space 1}   -2.03{col 65}{space 3}0.042{col 73}{space 4}-.1099411{col 86}{space 3}-.0019411
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0199439{col 45}{space 2} .0431411{col 56}{space 1}   -0.46{col 65}{space 3}0.644{col 73}{space 4}-.1045786{col 86}{space 3} .0646907
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0934547{col 45}{space 2} .0284835{col 56}{space 1}   -3.28{col 65}{space 3}0.001{col 73}{space 4}-.1493341{col 86}{space 3}-.0375753
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0947956{col 45}{space 2} .0415327{col 56}{space 1}    2.28{col 65}{space 3}0.023{col 73}{space 4} .0133162{col 86}{space 3}  .176275
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0651701{col 45}{space 2} .0245524{col 56}{space 1}   -2.65{col 65}{space 3}0.008{col 73}{space 4}-.1133373{col 86}{space 3}-.0170028
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0196337{col 45}{space 2} .0558613{col 56}{space 1}   -0.35{col 65}{space 3}0.725{col 73}{space 4}-.1292231{col 86}{space 3} .0899556
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2}-.0644422{col 45}{space 2} .0361406{col 56}{space 1}   -1.78{col 65}{space 3}0.075{col 73}{space 4}-.1353434{col 86}{space 3} .0064589
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0910779{col 45}{space 2}  .025581{col 56}{space 1}   -3.56{col 65}{space 3}0.000{col 73}{space 4}-.1412631{col 86}{space 3}-.0408927
{txt}{space 2}Melilla (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2}-.0315458{col 45}{space 2} .0646535{col 56}{space 1}   -0.49{col 65}{space 3}0.626{col 73}{space 4}-.1583839{col 86}{space 3} .0952923
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1689127{col 45}{space 2}  .110123{col 56}{space 1}    1.53{col 65}{space 3}0.125{col 73}{space 4}-.0471278{col 86}{space 3} .3849532
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,812
                                                {txt}F(3, 1808)        =  {res}     2.00
                                                {txt}Prob > F          = {res}    0.1126
                                                {txt}R-squared         = {res}    0.0044
                                                {txt}Root MSE          =    {res} .30099

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}  -.01271{col 33}{space 2} .0150646{col 44}{space 1}   -0.84{col 53}{space 3}0.399{col 61}{space 4}-.0422558{col 74}{space 3} .0168358
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0263778{col 33}{space 2} .0264628{col 44}{space 1}   -1.00{col 53}{space 3}0.319{col 61}{space 4}-.0782788{col 74}{space 3} .0255231
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1031055{col 33}{space 2} .0433572{col 44}{space 1}    2.38{col 53}{space 3}0.018{col 61}{space 4}   .01807{col 74}{space 3} .1881409
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  .102649{col 33}{space 2} .0100943{col 44}{space 1}   10.17{col 53}{space 3}0.000{col 61}{space 4} .0828514{col 74}{space 3} .1224466
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,339
                                                {txt}F(44, 1294)       =  {res}     2.35
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0771
                                                {txt}Root MSE          =    {res} .28017

{txt}{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}                  uncomfortable{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}cabine_use {c |}{col 33}{res}{space 2}-.0183448{col 45}{space 2} .0175216{col 56}{space 1}   -1.05{col 65}{space 3}0.295{col 73}{space 4}-.0527186{col 86}{space 3} .0160291
{txt}{space 23}pp_dummy {c |}{col 33}{res}{space 2}-.0384647{col 45}{space 2} .0299672{col 56}{space 1}   -1.28{col 65}{space 3}0.200{col 73}{space 4}-.0972544{col 86}{space 3}  .020325
{txt}{space 12}cabine_use_pp_dummy {c |}{col 33}{res}{space 2} .1133787{col 45}{space 2} .0470473{col 56}{space 1}    2.41{col 65}{space 3}0.016{col 73}{space 4} .0210814{col 86}{space 3}  .205676
{txt}{space 25}female {c |}{col 33}{res}{space 2} .0311622{col 45}{space 2} .0159121{col 56}{space 1}    1.96{col 65}{space 3}0.050{col 73}{space 4}-.0000541{col 86}{space 3} .0623786
{txt}{space 31} {c |}
{space 25}income {c |}
{space 9}Menos o igual a 300 €  {c |}{col 33}{res}{space 2} .0300808{col 45}{space 2} .0652583{col 56}{space 1}    0.46{col 65}{space 3}0.645{col 73}{space 4}-.0979428{col 86}{space 3} .1581045
{txt}{space 16}De 301 a 600 €  {c |}{col 33}{res}{space 2} .0721283{col 45}{space 2} .0400744{col 56}{space 1}    1.80{col 65}{space 3}0.072{col 73}{space 4}-.0064896{col 86}{space 3} .1507462
{txt}{space 16}De 601 a 900 €  {c |}{col 33}{res}{space 2}  .010969{col 45}{space 2} .0307556{col 56}{space 1}    0.36{col 65}{space 3}0.721{col 73}{space 4}-.0493673{col 86}{space 3} .0713053
{txt}{space 14}De 901 a 1.200 €  {c |}{col 33}{res}{space 2} .0136533{col 45}{space 2} .0285474{col 56}{space 1}    0.48{col 65}{space 3}0.633{col 73}{space 4} -.042351{col 86}{space 3} .0696575
{txt}{space 12}De 1.201 a 1.800 €  {c |}{col 33}{res}{space 2} .0074239{col 45}{space 2} .0280575{col 56}{space 1}    0.26{col 65}{space 3}0.791{col 73}{space 4}-.0476193{col 86}{space 3} .0624671
{txt}{space 12}De 1.801 a 2.400 €  {c |}{col 33}{res}{space 2}-.0359799{col 45}{space 2} .0305685{col 56}{space 1}   -1.18{col 65}{space 3}0.239{col 73}{space 4}-.0959492{col 86}{space 3} .0239894
{txt}{space 12}De 2.401 a 3.000 €  {c |}{col 33}{res}{space 2}-.0253633{col 45}{space 2} .0426416{col 56}{space 1}   -0.59{col 65}{space 3}0.552{col 73}{space 4}-.1090176{col 86}{space 3} .0582911
{txt}{space 12}De 3.001 a 4.500 €  {c |}{col 33}{res}{space 2} .0633382{col 45}{space 2} .0674992{col 56}{space 1}    0.94{col 65}{space 3}0.348{col 73}{space 4}-.0690816{col 86}{space 3}  .195758
{txt}{space 12}De 4.501 a 6.000 €  {c |}{col 33}{res}{space 2}-.0766968{col 45}{space 2} .0478098{col 56}{space 1}   -1.60{col 65}{space 3}0.109{col 73}{space 4}-.1704901{col 86}{space 3} .0170964
{txt}{space 16}Más de 6.000 €  {c |}{col 33}{res}{space 2}-.0733296{col 45}{space 2} .0423627{col 56}{space 1}   -1.73{col 65}{space 3}0.084{col 73}{space 4}-.1564367{col 86}{space 3} .0097776
{txt}{space 31} {c |}
{space 28}age {c |}{col 33}{res}{space 2}-.0013966{col 45}{space 2} .0031494{col 56}{space 1}   -0.44{col 65}{space 3}0.658{col 73}{space 4} -.007575{col 86}{space 3} .0047818
{txt}{space 25}age_sq {c |}{col 33}{res}{space 2} .0000186{col 45}{space 2} .0000334{col 56}{space 1}    0.56{col 65}{space 3}0.578{col 73}{space 4} -.000047{col 86}{space 3} .0000841
{txt}{space 31} {c |}
{space 22}education {c |}
{space 22}Primaria  {c |}{col 33}{res}{space 2}-.0877123{col 45}{space 2} .0923406{col 56}{space 1}   -0.95{col 65}{space 3}0.342{col 73}{space 4} -.268866{col 86}{space 3} .0934413
{txt}{space 11}Secundaria 1ª etapa  {c |}{col 33}{res}{space 2}-.0418042{col 45}{space 2} .0948906{col 56}{space 1}   -0.44{col 65}{space 3}0.660{col 73}{space 4}-.2279605{col 86}{space 3}  .144352
{txt}{space 11}Secundaria 2ª etapa  {c |}{col 33}{res}{space 2}-.0897669{col 45}{space 2} .0952645{col 56}{space 1}   -0.94{col 65}{space 3}0.346{col 73}{space 4}-.2766567{col 86}{space 3} .0971229
{txt}{space 26}F.P.  {c |}{col 33}{res}{space 2}-.0801297{col 45}{space 2} .0947682{col 56}{space 1}   -0.85{col 65}{space 3}0.398{col 73}{space 4}-.2660459{col 86}{space 3} .1057866
{txt}{space 20}Superiores  {c |}{col 33}{res}{space 2}-.0751099{col 45}{space 2} .0953992{col 56}{space 1}   -0.79{col 65}{space 3}0.431{col 73}{space 4} -.262264{col 86}{space 3} .1120442
{txt}{space 31} {c |}
{space 25}TAMUNI {c |}
{space 5}2.001 a 10.000 habitantes  {c |}{col 33}{res}{space 2} .0534308{col 45}{space 2} .0370467{col 56}{space 1}    1.44{col 65}{space 3}0.149{col 73}{space 4}-.0192474{col 86}{space 3}  .126109
{txt}{space 4}10.001 a 50.000 habitantes  {c |}{col 33}{res}{space 2} .0181848{col 45}{space 2} .0327067{col 56}{space 1}    0.56{col 65}{space 3}0.578{col 73}{space 4}-.0459793{col 86}{space 3} .0823488
{txt}{space 3}50.001 a 100.000 habitantes  {c |}{col 33}{res}{space 2} .0041236{col 45}{space 2} .0377308{col 56}{space 1}    0.11{col 65}{space 3}0.913{col 73}{space 4}-.0698967{col 86}{space 3} .0781438
{txt}{space 2}100.001 a 400.000 habitantes  {c |}{col 33}{res}{space 2}-.0089218{col 45}{space 2} .0338759{col 56}{space 1}   -0.26{col 65}{space 3}0.792{col 73}{space 4}-.0753794{col 86}{space 3} .0575358
{txt}400.001 a 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.0411764{col 45}{space 2}  .036089{col 56}{space 1}   -1.14{col 65}{space 3}0.254{col 73}{space 4}-.1119758{col 86}{space 3}  .029623
{txt}{space 3}Más de 1.000.000 habitantes  {c |}{col 33}{res}{space 2}-.1061396{col 45}{space 2} .0427908{col 56}{space 1}   -2.48{col 65}{space 3}0.013{col 73}{space 4}-.1900865{col 86}{space 3}-.0221926
{txt}{space 31} {c |}
{space 27}CCAA {c |}
{space 24}Aragón  {c |}{col 33}{res}{space 2}-.0226798{col 45}{space 2} .0356533{col 56}{space 1}   -0.64{col 65}{space 3}0.525{col 73}{space 4}-.0926243{col 86}{space 3} .0472647
{txt}{space 6}Asturias (Principado de)  {c |}{col 33}{res}{space 2} .0555926{col 45}{space 2} .0541499{col 56}{space 1}    1.03{col 65}{space 3}0.305{col 73}{space 4}-.0506386{col 86}{space 3} .1618239
{txt}{space 15}Balears (Illes)  {c |}{col 33}{res}{space 2} .0519255{col 45}{space 2} .0515653{col 56}{space 1}    1.01{col 65}{space 3}0.314{col 73}{space 4}-.0492352{col 86}{space 3} .1530862
{txt}{space 22}Canarias  {c |}{col 33}{res}{space 2}-.0616985{col 45}{space 2} .0342666{col 56}{space 1}   -1.80{col 65}{space 3}0.072{col 73}{space 4}-.1289226{col 86}{space 3} .0055257
{txt}{space 21}Cantabria  {c |}{col 33}{res}{space 2}-.0360148{col 45}{space 2} .0366573{col 56}{space 1}   -0.98{col 65}{space 3}0.326{col 73}{space 4} -.107929{col 86}{space 3} .0358994
{txt}{space 12}Castilla-La Mancha  {c |}{col 33}{res}{space 2} .1243095{col 45}{space 2} .0596034{col 56}{space 1}    2.09{col 65}{space 3}0.037{col 73}{space 4} .0073797{col 86}{space 3} .2412393
{txt}{space 15}Castilla y León  {c |}{col 33}{res}{space 2}   .08527{col 45}{space 2} .0554282{col 56}{space 1}    1.54{col 65}{space 3}0.124{col 73}{space 4} -.023469{col 86}{space 3} .1940091
{txt}{space 22}Cataluña  {c |}{col 33}{res}{space 2} .0081064{col 45}{space 2} .0351607{col 56}{space 1}    0.23{col 65}{space 3}0.818{col 73}{space 4}-.0608717{col 86}{space 3} .0770846
{txt}{space 10}Comunitat Valenciana  {c |}{col 33}{res}{space 2}-.0548594{col 45}{space 2} .0275512{col 56}{space 1}   -1.99{col 65}{space 3}0.047{col 73}{space 4}-.1089093{col 86}{space 3}-.0008096
{txt}{space 19}Extremadura  {c |}{col 33}{res}{space 2}-.0205087{col 45}{space 2} .0433248{col 56}{space 1}   -0.47{col 65}{space 3}0.636{col 73}{space 4}-.1055033{col 86}{space 3} .0644859
{txt}{space 23}Galicia  {c |}{col 33}{res}{space 2}-.0927203{col 45}{space 2} .0284846{col 56}{space 1}   -3.26{col 65}{space 3}0.001{col 73}{space 4}-.1486014{col 86}{space 3}-.0368392
{txt}{space 9}Madrid (Comunidad de)  {c |}{col 33}{res}{space 2} .0959428{col 45}{space 2} .0415143{col 56}{space 1}    2.31{col 65}{space 3}0.021{col 73}{space 4} .0145002{col 86}{space 3} .1773855
{txt}{space 12}Murcia (Región de)  {c |}{col 33}{res}{space 2}-.0648615{col 45}{space 2} .0246326{col 56}{space 1}   -2.63{col 65}{space 3}0.009{col 73}{space 4}-.1131857{col 86}{space 3}-.0165372
{txt}{space 2}Navarra (Comunidad Foral de)  {c |}{col 33}{res}{space 2}-.0155878{col 45}{space 2} .0559227{col 56}{space 1}   -0.28{col 65}{space 3}0.780{col 73}{space 4}-.1252969{col 86}{space 3} .0941214
{txt}{space 20}País Vasco  {c |}{col 33}{res}{space 2} -.060398{col 45}{space 2} .0363261{col 56}{space 1}   -1.66{col 65}{space 3}0.097{col 73}{space 4}-.1316625{col 86}{space 3} .0108665
{txt}{space 20}Rioja (La)  {c |}{col 33}{res}{space 2}-.0924871{col 45}{space 2} .0257756{col 56}{space 1}   -3.59{col 65}{space 3}0.000{col 73}{space 4}-.1430537{col 86}{space 3}-.0419204
{txt}{space 4}Ceuta (Ciudad Autónoma de)  {c |}{col 33}{res}{space 2} .0907419{col 45}{space 2} .0812237{col 56}{space 1}    1.12{col 65}{space 3}0.264{col 73}{space 4}-.0686027{col 86}{space 3} .2500865
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2} .1605457{col 45}{space 2} .1108972{col 56}{space 1}    1.45{col 65}{space 3}0.148{col 73}{space 4}-.0570122{col 86}{space 3} .3781036
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 7 2}
(variable
{bf:Controls} was {bf:str13}, now {bf:str16} to accommodate using data's values)
{p_end}
{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

Linear regression                               Number of obs     = {res}     1,830
                                                {txt}F(3, 1826)        =  {res}     2.32
                                                {txt}Prob > F          = {res}    0.0731
                                                {txt}R-squared         = {res}    0.0054
                                                {txt}Root MSE          =    {res} .30312

{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}      uncomfortable{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}cabine_use {c |}{col 21}{res}{space 2}-.0101364{col 33}{space 2} .0150643{col 44}{space 1}   -0.67{col 53}{space 3}0.501{col 61}{space 4}-.0396816{col 74}{space 3} .0194087
{txt}{space 11}pp_dummy {c |}{col 21}{res}{space 2}-.0256128{col 33}{space 2} .0266439{col 44}{space 1}   -0.96{col 53}{space 3}0.337{col 61}{space 4}-.0778685{col 74}{space 3}  .026643
{txt}cabine_use_pp_dummy {c |}{col 21}{res}{space 2} .1109911{col 33}{space 2} .0438211{col 44}{space 1}    2.53{col 53}{space 3}0.011{col 61}{space 4} .0250465{col 74}{space 3} .1969358
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .1025358{col 33}{space 2} .0100837{col 44}{space 1}   10.17{col 53}{space 3}0.000{col 61}{space 4} .0827591{col 74}{space 3} .1223125
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}{p 0 4 2}
file {bf}
01_data/survey_ccaa_jk_2.dta{rm}
saved
{p_end}

{com}. 
{txt}end of do-file

{com}. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"
{txt}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/cabinas_jop_log.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}19 Sep 2023, 12:41:43
{txt}{.-}
{smcl}
{txt}{sf}{ul off}